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Class List

Here are the classes, structs, unions and interfaces with brief descriptions:
itk::AbortCheckEvent
itk::AbortEvent
itk::Function::Abs< TInput, TOutput >
itk::AbsImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_abs() of its pixels
itk::AbsImageFilter< TInputImage, TOutputImage >Computes the ABS(x) pixel-wise
itk::Functor::AbsoluteValueDifference2< TInput1, TInput2, TOutput >
itk::AbsoluteValueDifferenceImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements pixel-wise the computation of absolute value difference
itk::Accessor::AbsPixelAccessor< TInternalType, TExternalType >Give access to the vcl_abs() function of a value
itk::Functor::AccessorFunctor< TInput, TAccessor >Convert an accessor to a functor so that it can be used in a UnaryFunctorImageFilter
itk::AccumulateImageFilter< TInputImage, TOutputImage >Implements an accumulation of an image along a selected direction
itk::Functor::Acos< TInput, TOutput >
itk::AcosImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_acos() of its pixels
itk::AcosImageFilter< TInputImage, TOutputImage >Computes the vcl_acos(x) pixel-wise
itk::Accessor::AcosPixelAccessor< TInternalType, TExternalType >Give access to the vcl_acos() function of a value
itk::ActiveShapeModelCalculator< TImage >Base class for ActiveShapeModelCalculator object
itk::ActiveShapeModelGradientSearchMethod< TImage >Base class for ActiveShapeModelGradientSearchMethod object
itk::AdaptImageFilter< TInputImage, TOutputImage, TAccessor >Convert an image to another pixel type using the specified data accessor
itk::AdaptiveHistogramEqualizationImageFilter< TImageType >Power Law Adaptive Histogram Equalization
itk::Functor::Add1< TInput, TOutput >
itk::Functor::Add2< TInput1, TInput2, TOutput >
itk::Function::Add3< TInput1, TInput2, TInput3, TOutput >
itk::Functor::AddConstantTo< TInput, TConstant, TOutput >
itk::AddConstantToImageFilter< TInputImage, TConstant, TOutputImage >Add a constant to all input pixels
itk::AddImageAdaptor< TImage >Presents an image as being the addition of a constant value to all pixels
itk::AddImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements an operator for pixel-wise addition of two images
itk::Concept::AdditiveOperators< T1, T2, T3 >
itk::Accessor::AddPixelAccessor< TPixel >Simulates the effect of adding a constant value to all pixels
itk::AffineGeometryFrame< TScalarType, NDimensions >Describes the geometry of a data object
itk::AffineTransform< TScalarType, NDimensions >
itk::AggregateLabelMapFilter< TImage >Collapses all labels into the first label
itk::AmoebaOptimizerWrap of the vnl_amoeba algorithm
itk::AnalyzeImageIOClass that defines how to read Analyze file format. Analyze IMAGE FILE FORMAT - As much information as I can determine from the Medical image formats web site, and the Analyze75.pdf file provided from the Mayo clinic. A special note of thanks to Dennis P. Hanson (dph@mayo.edu) for his generous contributions in getting this information correct
itk::AnalyzeImageIOFactoryCreate instances of AnalyzeImageIO objects using an object factory
itk::AnchorCloseImageFilter< TImage, TKernel >
itk::AnchorDilateImageFilter< TImage, TKernel >
itk::AnchorErodeDilateImageFilter< TImage, TKernel, TFunction1, TFunction2 >Class to implement erosions and dilations using anchor methods. This is the base class that must be instantiated with appropriate definitions of greater, less and so on. The SetBoundary facility isn't necessary for operation of the anchor method but is included for compatability with other morphology classes in itk
itk::AnchorErodeDilateLine< TInputPix, TFunction1, TFunction2 >Class to implement erosions and dilations using anchor methods. This is the base class that must be instantiated with appropriate definitions of greater, less and so on. There is special code for cases where the structuring element is bigger than the image size that aren't particularly anchor related, but use the same data structures. Hopefully these sections occupy a very minor proportion of the time
itk::AnchorErodeImageFilter< TImage, TKernel >
itk::AnchorOpenCloseImageFilter< TImage, TKernel, LessThan, GreaterThan, LessEqual, GreaterEqual >Class to implement openings and closings using anchor methods
itk::AnchorOpenCloseLine< TInputPix, THistogramCompare, TFunction1, TFunction2 >Class to implement openings and closings using anchor methods. This is the base class that must be instantiated with appropriate definitions of greater, less and so on
itk::AnchorOpenImageFilter< TImage, TKernel >
AnchorUtilitiesFunctionality in common for anchor openings/closings and erosions/dilation
itk::Functor::AND< TInput1, TInput2, TOutput >
itk::AndImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements the AND logical operator pixel-wise between two images
itk::AnisotropicDiffusionFunction< TImage >
itk::AnisotropicDiffusionImageFilter< TInputImage, TOutputImage >
itk::AnisotropicFourthOrderLevelSetImageFilter< TInputImage, TOutputImage >This class implements the 4th-order level set anisotropic diffusion (smoothing) PDE
itk::AnnulusOperator< TPixel, TDimension, TAllocator >A NeighborhoodOperator for performing a matched filtering with an annulus (two concentric circles, spheres, hyperspheres, etc.)
itk::AntiAliasBinaryImageFilter< TInputImage, TOutputImage >
itk::AnyEvent
itk::ApproximateSignedDistanceMapImageFilter< TInputImage, TOutputImage >Create a map of the approximate signed distance from the boundaries of a binary image
itk::ArchetypeSeriesFileNamesGenerate an ordered sequence of filenames
itk::AreaClosingImageFilter< TInputImage, TOutputImage, TAttribute >Morphological closing by attributes
itk::AreaOpeningImageFilter< TInputImage, TOutputImage, TAttribute >Morphological opening by attributes
itk::Array< TValueType >Array class with size defined at construction time
itk::Array2D< TValueType >Array2D class representing a 2D array with size defined at construction time
itk::ArrowSpatialObject< TDimension >Representation of a Arrow based on the spatial object classes
itk::Functor::Asin< TInput, TOutput >
itk::AsinImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_asin() of its pixels
itk::AsinImageFilter< TInputImage, TOutputImage >Computes the vcl_asin(x) pixel-wise
itk::Accessor::AsinPixelAccessor< TInternalType, TExternalType >Give access to the vcl_asin() function of a value
itk::Concept::Assignable< T >
itk::Functor::Atan< TInput, TOutput >
itk::Functor::Atan2< TInput1, TInput2, TOutput >
itk::Atan2ImageFilter< TInputImage1, TInputImage2, TOutputImage >Computes arctangent pixel-wise from two images
itk::AtanImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_atan() of its pixels
itk::AtanImageFilter< TInputImage, TOutputImage >Computes the vcl_atan(x) pixel-wise
itk::Accessor::AtanPixelAccessor< TInternalType, TExternalType >Give access to the vcl_atan() function of a value
itk::AtanRegularizedHeavisideStepFunction< TInput, TOutput >Atan-based implementation of the Regularized (smoothed) Heaviside functions
itk::AttributeMorphologyBaseImageFilter< TInputImage, TOutputImage, TAttribute, TFunction >Morphological opening by attributes
itk::AuthalicMatrixCoefficients< TInputMesh >Compute a matrix filled with Authalic Coefiicients of the edge, wherever two vertices are connected with an edge
itk::AutoCropLabelMapFilter< TInputImage >Crop a LabelMap image to fit exactly the objects in the LabelMap
itk::AutomaticTopologyMeshSource< TOutputMesh >Convenience class for generating meshes
itk::AutoPointer< TObjectType >Implements an Automatic Pointer to an object
itk::AutoPointerDataObjectDecorator< T >Decorates any pointer to a simple object with a DataObject API using AutoPointer semantics
itk::Functor::AutumnColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::AuxVarTypeDefault< TPixel, VAuxDimension, VSetDimension >Level set auxiliary variables type information
itk::FastMarchingImageFilter< TLevelSet, TSpeedImage >::AxisNodeType
itk::AzimuthElevationToCartesianTransform< TScalarType, NDimensions >Transforms from an azimuth, elevation, radius coordinate system to a Cartesian coordinate system, or vice versa
itk::Statistics::BackPropagationLayer< TMeasurementVector, TTargetVector >
itk::BackwardDifferenceOperator< TPixel, TDimension, TAllocator >Operator whose inner product with a neighborhood returns a "half" derivative at the center of the neighborhood
itk::BalloonForceFilter< TInputMesh, TOutputMesh >BalloonForceFilter is used to apply balloon force and the potential force onto the 2D surface model embedded in a 3D space
itk::BandNode< TIndexType, TDataType >
itk::BarrierStandard barrier class implementation for synchronizing the execution of threads
itk::BarycentricCombination< TPointContainer, TWeightContainer >
itk::BasicDilateImageFilter< TInputImage, TOutputImage, TKernel >Gray scale dilation of an image
itk::BasicErodeImageFilter< TInputImage, TOutputImage, TKernel >Gray scale erosion of an image
itk::Statistics::BatchSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >
itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >Performs Bayesian Classification on an image
itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >This filter is intended to be used as a helper class to initialize the BayesianClassifierImageFilter. The goal of this filter is to generate a membership image that indicates the membership of each pixel to each class. These membership images are fed as input to the bayesian classfier filter
itk::BilateralImageFilter< TInputImage, TOutputImage >Blurs an image while preserving edges
itk::Function::BinaryAccumulator< TInputPixel, TOutputPixel >
itk::BinaryBallStructuringElement< TPixel, VDimension, TAllocator >A Neighborhood that represents a ball structuring element (ellipsoid) with binary elements
itk::ImageToImageFilterDetail::BinaryBooleanDispatch< B1, B2 >Templated class to produce a unique type for a pairing of booleans
itk::BinaryContourImageFilter< TInputImage, TOutputImage >Labels the pixels on the border of the objects in a binary image
itk::BinaryCrossStructuringElement< TPixel, VDimension, TAllocator >A Neighborhood that represents a cross structuring element with binary elements
itk::BinaryDilateImageFilter< TInputImage, TOutputImage, TKernel >Fast binary dilation
itk::Functor::BinaryElongationLabelObjectAccessor< TLabelObject >
itk::BinaryErodeImageFilter< TInputImage, TOutputImage, TKernel >Fast binary erosion
itk::Functor::BinaryFlatnessLabelObjectAccessor< TLabelObject >
itk::BinaryFunctorImageFilter< TInputImage1, TInputImage2, TOutputImage, TFunction >Implements pixel-wise generic operation of two images
itk::BinaryImageToLabelMapFilter< TInputImage, TOutputImage >Label the connected components in a binary image and produce a collection of label objects
itk::BinaryImageToShapeLabelMapFilter< TInputImage, TOutputImage >Converts a binary image to a label map and valuate the shape attributes
itk::BinaryImageToStatisticsLabelMapFilter< TInputImage, TFeatureImage, TOutputImage >Convenient class to convert a binary image to a label map and valuate the statistics attributes at once
itk::ImageToImageFilterDetail::BinaryIntDispatch< D1, D2 >Templated class to produce a unique type for a pairing of integers
itk::BinaryMagnitudeImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements pixel-wise the computation of square root of the sum of squares
itk::BinaryMask3DMeshSource< TInputImage, TOutputMesh >
itk::BinaryMaskToNarrowBandPointSetFilter< TInputImage, TOutputMesh >Generate a PointSet containing the narrow band around the edges of a input binary image
itk::BinaryMedialNodeMetric< VDimensions >
itk::BinaryMedianImageFilter< TInputImage, TOutputImage >Applies an version of the median filter optimized for binary images
itk::BinaryMinMaxCurvatureFlowFunction< TImage >
itk::BinaryMinMaxCurvatureFlowImageFilter< TInputImage, TOutputImage >Denoise a binary image using min/max curvature flow
itk::BinaryMorphologicalClosingImageFilter< TInputImage, TOutputImage, TKernel >Binary morphological closing of an image
itk::BinaryMorphologicalOpeningImageFilter< TInputImage, TOutputImage, TKernel >Binary morphological closing of an image
itk::BinaryMorphologyImageFilter< TInputImage, TOutputImage, TKernel >Base class for fast binary dilation and erosion
itk::Functor::BinaryPrincipalAxesLabelObjectAccessor< TLabelObject >
itk::Functor::BinaryPrincipalMomentsLabelObjectAccessor< TLabelObject >
itk::BinaryProjectionImageFilter< TInputImage, TOutputImage >Binary projection
itk::BinaryPruningImageFilter< TInputImage, TOutputImage >This filter removes "spurs" of less than a certain length in the input image
itk::BinaryShapeKeepNObjectsImageFilter< TInputImage >Keep N objects according to their shape attributes
itk::BinaryShapeOpeningImageFilter< TInputImage >Remove objects based on the value of their shape attribute
itk::BinaryStatisticsKeepNObjectsImageFilter< TInputImage, TFeatureImage >Keep N objects according to their statistics attributes
itk::BinaryStatisticsOpeningImageFilter< TInputImage, TFeatureImage >Remove objects based on the value of their Statistics attribute
itk::BinaryThinningImageFilter< TInputImage, TOutputImage >This filter computes one-pixel-wide edges of the input image
itk::Functor::BinaryThreshold< TInput, TOutput >
itk::Function::BinaryThresholdAccumulator< TInputPixel, TOutputPixel >
itk::BinaryThresholdImageFilter< TInputImage, TOutputImage >Binarize an input image by thresholding
itk::BinaryThresholdImageFunction< TInputImage, TCoordRep >Returns true is the value of an image lies within a range of thresholds This ImageFunction returns true (or false) if the pixel value lies within (outside) a lower and upper threshold value. The threshold range can be set with the ThresholdBelow, ThresholdBetween or ThresholdAbove methods. The input image is set via method SetInputImage()
itk::BinaryThresholdProjectionImageFilter< TInputImage, TOutputImage >BinaryThreshold projection
itk::BinaryThresholdSpatialFunction< TFunction >A spatial functions that returns if the internal spatial function is within user specified thresholds
itk::ImageToImageFilterDetail::BinaryUnsignedIntDispatch< D1, D2 >Templated class to produce a unique type for a pairing of unsigned integers (usually two dimensions)
itk::BinomialBlurImageFilter< TInputImage, TOutputImage >Performs a separable blur on each dimension of an image
itk::BioRadImageIOImageIO class for reading Bio-Rad images. Bio-Rad file format are used by confocal micropscopes like MRC 1024, MRC 600 http://www.bio-rad.com/
itk::BioRadImageIOFactoryCreate instances of BioRadImageIO objects using an object factory
itk::Function::BlackmanWindowFunction< VRadius, TInput, TOutput >Window function for sinc interpolation.

\[ w(x) = 0.42 + 0.5 cos(\frac{\pi x}{m}) + 0.08 cos(\frac{2 \pi x}{m}) \]

itk::BlackTopHatImageFilter< TInputImage, TOutputImage, TKernel >Black top hat extract local minima that are larger than the structuring element
itk::BlobSpatialObject< TDimension >Spatial object representing a potentially amorphous object
itk::BloxBoundaryPointImage< TImageDimension >Templated n-dimensional image class used to store linked lists
itk::BloxBoundaryPointImageToBloxBoundaryProfileImageFilter< TSourceImage >Converts a BloxImage of BloxBoundaryPoints to a BloxImage of BloxBoundaryProfiles
itk::BloxBoundaryPointItem< VImageDimension >A boundary point, stored in a BloxPixel
itk::BloxBoundaryPointPixel< NDimensions >Holds a linked list of itk::BloxBoundaryPointItem's
itk::BloxBoundaryPointToCoreAtomImageFilter< dim >Converts a gradient image to an BloxImage of BloxBoundaryPoints
itk::BloxBoundaryProfileImage< TImageDimension >N-dimensional image class which handles BloxBoundaryProfileItems
itk::BloxBoundaryProfileImageToBloxCoreAtomImageFilter< TInputImage, TOutputImage, TSourceImage >Converts a blox boundary profile image to an image of core atoms
itk::BloxBoundaryProfileItem< TImageDimension >
itk::BloxBoundaryProfilePixel< NDimensions >
itk::BloxCoreAtomImage< NDimension >N-dimensional image class which handles BloxCoreAtomItems
itk::BloxCoreAtomItem< VImageDimension >A core atom object, stored in a BloxPixel
itk::BloxCoreAtomPixel< NDimensions >Holds a linked list of itk::BloxCoreAtomItem's
itk::BloxImage< TBloxPixelType, TImageDimension >Templated n-dimensional image class used to store linked lists
itk::BloxItemAn entry in the BloxPixel linked list
itk::BloxPixel< TItemType >Holds a linked list of BloxItem's
itk::Functor::BlueColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::BluePixelAccessor< T >Give access to the Blue component of a RGBPixel type
itk::BMPImageIORead BMPImage file format
itk::BMPImageIOFactoryCreate instances of BMPImageIO objects using an object factory
itk::ImageToImageFilterDetail::BooleanDispatch< bool >Templated class to produce a unique type "true" and "false"
itk::watershed::Boundary< TScalarType, TDimension >
itk::Mesh< TPixelType, VDimension, TMeshTraits >::BoundaryAssignmentIdentifier
itk::watershed::BoundaryResolver< TPixelType, TDimension >
itk::Functor::BoundedReciprocal< TInput, TOutput >
itk::BoundedReciprocalImageFilter< TInputImage, TOutputImage >Computes 1/(1+x) for each pixel in the image
itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >Represent and compute information about bounding boxes
itk::BoxImageFilter< TInputImage, TOutputImage >A base class for all the filters working on a box neighborhood
itk::BoxMeanImageFilter< TInputImage, TOutputImage >Implements a fast rectangular mean filter using the accumulator approach
itk::BoxSigmaImageFilter< TInputImage, TOutputImage >Implements a fast rectangular sigma filter using the accumulator approach
itk::BoxSpatialObject< TDimension >The class may be used to represent N-dimensional boxes. In two dimensions it is a rectangle, In three dimensions it is a cuboid..
itk::Concept::BracketOperator< T1, T2, T3 >
itk::Brains2HeaderFactoryCreate instances of Brains2Header objects using an object factory
itk::Brains2IPLHeaderInfo
itk::Brains2MaskHeaderInfo
itk::Brains2MaskImageIOClass that defines how to read Brains2Mask file format
itk::Brains2MaskImageIOFactoryCreate instances of Brains2MaskImageIO objects using an object factory
itk::BresenhamLine< VDimension >
itk::Bruker2DSEQImageIOClass that defines how to read Bruker file format. Bruker IMAGE FILE FORMAT - The following is a brief description of the Bruker file format taken from:
itk::Bruker2DSEQImageIOFactoryCreate instances of Bruker2DSEQImageIO objects using an object factory
itk::BSplineCenteredL2ResampleImageFilterBase< TInputImage, TOutputImage >
itk::BSplineCenteredResampleImageFilterBase< TInputImage, TOutputImage >Evaluates the Centered B-Spline interpolation of an image. Spline order may be from 0 to 5
itk::BSplineDecompositionImageFilter< TInputImage, TOutputImage >Calculates the B-Spline coefficients of an image. Spline order may be from 0 to 5
itk::BSplineDeformableTransform< TScalarType, NDimensions, VSplineOrder >Deformable transform using a BSpline representation
itk::BSplineDeformableTransformInitializer< TTransform, TImage >BSplineDeformableTransformInitializer is a helper class intended to initialize the grid parameters of a BSplineDeformableTransform based on the parameters of an image
itk::BSplineDerivativeKernelFunction< VSplineOrder >Derivative of a BSpline kernel used for density estimation and nonparameteric regression
itk::BSplineDownsampleImageFilter< TInputImage, TOutputImage, ResamplerType >Down-samples an image by a factor of 2 using B-Spline filter interpolation
itk::BSplineInterpolateImageFunction< TImageType, TCoordRep, TCoefficientType >Evaluates the B-Spline interpolation of an image. Spline order may be from 0 to 5
itk::BSplineInterpolationWeightFunction< TCoordRep, VSpaceDimension, VSplineOrder >Returns the weights over the support region used for B-spline interpolation/reconstruction
itk::BSplineKernelFunction< VSplineOrder >BSpline kernel used for density estimation and nonparameteric regression
itk::BSplineL2ResampleImageFilterBase< TInputImage, TOutputImage >Uses the "Centered l2" B-Spline pyramid implementation of B-Spline Filters to up/down sample an image by a factor of 2
itk::BSplineResampleImageFilterBase< TInputImage, TOutputImage >Uses the "l2" spline pyramid implementation of B-Spline Filters to up/down sample an image by a factor of 2
itk::BSplineResampleImageFunction< TImageType, TCoordRep >Resample image intensity from a BSpline coefficient image
itk::BSplineScatteredDataPointSetToImageFilter< TInputPointSet, TOutputImage >Image filter which provides a B-spline output approximation
itk::BSplineUpsampleImageFilter< TInputImage, TOutputImage, ResamplerType >Uses B-Spline interpolation to upsample an image by a factor of 2. This class is the public interface for spline upsampling as defined by the ResamplerType
itk::ByteSwapper< T >Perform machine dependent byte swapping
itk::CacheableScalarFunctionFunction cache implementation
itk::NeighborhoodAlgorithm::CalculateOutputWrapOffsetModifiers< TImage >
itk::VTKImageExportBase::CallbackTypeProxy
itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate
itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector
itk::CannyEdgeDetectionImageFilter< TInputImage, TOutputImage >
itk::CannySegmentationLevelSetFunction< TImageType, TFeatureImageType >A refinement of the standard level-set function which computes a speed term and advection term based on pseudo-Canny edges. See CannySegmentationLevelSetImageFilter for complete information
itk::CannySegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in images based on image features derived from pseudo-canny-edges
itk::Functor::Cast< TInput, TOutput >
itk::CastImageFilter< TInputImage, TOutputImage >Casts input pixels to output pixel type
itk::bio::Cell< NSpaceDimension >This class implement the minimal behavior of a biological cell. The basic behavior of a cell is related with the cell cycle. Geometrical concepts like size and shape are also managed by this abstract cell
itk::bio::CellBaseNon-templated Base class from which the templated Cell classes will be derived. Derived classes are instantiated for a specific space dimension
itk::CellInterface< TPixelType, TCellTraits >
itk::CellInterfaceVisitor< TPixelType, TCellTraits >
itk::CellInterfaceVisitorImplementation< TPixelType, TCellTraits, CellTopology, UserVisitor >
itk::CellTraitsInfo< VPointDimension, TCoordRep, TInterpolationWeight, TPointIdentifier, TCellIdentifier, TCellFeatureIdentifier, TPoint, TPointsContainer, TUsingCellsContainer >A simple utility class to define the cell type inside a mesh type structure definition. This just makes a copy of existing type information that is needed for a cell type template parameter
itk::bio::CellularAggregate< NSpaceDimension >This class represent an aggregation of bio::Cell objects This class is the base for different types of cellular groups including bacterial colonies and pluricellular organisms
itk::bio::CellularAggregateBaseBase class for the CellularAggregates. This base class is not templated over the space dimension
itk::CenteredAffineTransform< TScalarType, NDimensions >Affine transformation with a specified center of rotation
itk::CenteredEuler3DTransform< TScalarType >CenteredEuler3DTransform of a vector space (e.g. space coordinates)
itk::CenteredRigid2DTransform< TScalarType >CenteredRigid2DTransform of a vector space (e.g. space coordinates)
itk::CenteredSimilarity2DTransform< TScalarType >CenteredSimilarity2DTransform of a vector space (e.g. space coordinates)
itk::CenteredTransformInitializer< TTransform, TFixedImage, TMovingImage >CenteredTransformInitializer is a helper class intended to initialize the center of rotation and the translation of Transforms having the center of rotation among their parameters
itk::CenteredVersorTransformInitializer< TFixedImage, TMovingImage >CenteredVersorTransformInitializer is a helper class intended to initialize the center of rotation, versor, and translation of the VersorRigid3DTransform
itk::Functor::CenterOfGravityLabelObjectAccessor< TLabelObject >
itk::CentralDifferenceImageFunction< TInputImage, TCoordRep >Calculate the derivative by central differencing
itk::Functor::CentroidLabelObjectAccessor< TLabelObject >
itk::ChainCodePath< VDimension >Represent a path as a sequence of connected image index offsets
itk::ChainCodePath2DRepresent a 2D path as a sequence of connected image index offsets
itk::ChainCodeToFourierSeriesPathFilter< TInputChainCodePath, TOutputFourierSeriesPath >Filter that produces a Fourier series version of a chain code path
itk::ChangeInformationImageFilter< TInputImage >Change the origin, spacing and/or region of an Image
itk::Functor::ChangeLabel< TInput, TOutput >
itk::ChangeLabelImageFilter< TInputImage, TOutputImage >Change Sets of Labels
itk::ChangeLabelLabelMapFilter< TImage >Replace the label Ids of selected LabelObjects with new label Ids
itk::ChangeRegionLabelMapFilter< TInputImage >Change the region of a label map
itk::CheckerBoardImageFilter< TImage >Combines two images in a checkerboard pattern
itk::ChildTreeIterator< TTreeType >
itk::Statistics::ChiSquareDistributionChiSquareDistribution class defines the interface for a univariate Chi-Square distribution (pdfs, cdfs, etc.)
itk::ClassifierBase< TDataContainer >Base class for classifier object
classname
itk::ClosingByReconstructionImageFilter< TInputImage, TOutputImage, TKernel >Closing by reconstruction of an image
itk::MultivariateLegendrePolynomial::CoefficientVectorSizeMismatch
itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >Selects a region of space where two independent fronts run towards each other
itk::Functor::ColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::ColorTable< TPixel >
itk::CommandSuperclass for callback/observer methods
itk::Concept::Comparable< T1, T2 >
itk::CompareHistogramImageToImageMetric< TFixedImage, TMovingImage >Compares Histograms between two images to be registered to a Training Histogram
itk::Statistics::CompletelyConnectedWeightSet< TMeasurementVector, TTargetVector >
itk::ComplexBSplineInterpolateImageFunction< TImageType, TCoordRep, TCoefficientType >Complex wrapper around BSplineInterpolateImageFunction
itk::Function::ComplexToImaginary< TInput, TOutput >
itk::ComplexToImaginaryImageAdaptor< TImage, TOutputPixelType >Presents a complex image as being composed of imag() part of its pixels
itk::ComplexToImaginaryImageFilter< TInputImage, TOutputImage >Computes pixel-wise the imaginary part of a complex image
itk::Accessor::ComplexToImaginaryPixelAccessor< TInternalType, TExternalType >Give access to the Imaginary part of a std::complex<> value
itk::Function::ComplexToModulus< TInput, TOutput >
itk::ComplexToModulusImageAdaptor< TImage, TOutputPixelType >Presents a complex image as being composed of vcl_abs() part of its pixels
itk::ComplexToModulusImageFilter< TInputImage, TOutputImage >Computes pixel-wise the Modulus of a complex image
itk::Accessor::ComplexToModulusPixelAccessor< TInternalType, TExternalType >Give access to the Modulus of a std::complex<> value
itk::Function::ComplexToPhase< TInput, TOutput >
itk::ComplexToPhaseImageAdaptor< TImage, TOutputPixelType >Presents a complex image as being composed of arg() part of its pixels
itk::ComplexToPhaseImageFilter< TInputImage, TOutputImage >Computes pixel-wise the modulus of a complex image
itk::Accessor::ComplexToPhasePixelAccessor< TInternalType, TExternalType >Give access to the Phase part of a std::complex<> value
itk::Function::ComplexToReal< TInput, TOutput >
itk::ComplexToRealImageAdaptor< TImage, TOutputPixelType >Presents a complex image as being composed of real() part of its pixels
itk::ComplexToRealImageFilter< TInputImage, TOutputImage >Computes pixel-wise the real(x) part of a complex image
itk::Accessor::ComplexToRealPixelAccessor< TInternalType, TExternalType >Give access to the Real part of a std::complex<> value
itk::Function::Compose2DCovariantVector< TInput >
itk::Compose2DCovariantVectorImageFilter< TInputImage, TOutputImage >Implements pixel-wise composition of an 2D covariant vector pixel from two scalar images
itk::Function::Compose2DVector< TInput >
itk::Compose2DVectorImageFilter< TInputImage, TOutputImage >Implements pixel-wise composition of an 2D vector pixel from two scalar images
itk::Function::Compose3DCovariantVector< TInput >
itk::Compose3DCovariantVectorImageFilter< TInputImage, TOutputImage >Implements pixel-wise composition of an 3D covariant vector pixel from three scalar images
itk::Function::Compose3DVector< TInput >
itk::Compose3DVectorImageFilter< TInputImage, TOutputImage >Implements pixel-wise composition of an 3D vector pixel from three scalar images
itk::Function::ComposeRGB< TInput >
itk::Functor::ComposeRGBA< TInput >
itk::ComposeRGBAImageFilter< TInputImage, TOutputImage >Implements pixel-wise composition of an RGBA pixel from four scalar images
itk::ComposeRGBImageFilter< TInputImage, TOutputImage >Implements pixel-wise composition of an RGB pixel from three scalar images
itk::CompositeValleyFunctionMultiple valley shaped curve function
itk::ConditionalConstIterator< TImage >ConditionalConstIterator is a base class for other iterators where membership in the set of output pixels is "conditional" upon some property, calculation, etc. For example, a threshold iterator might walk a region and return only those pixels which meet a minimum intensity condition
itk::ConditionVariableA thread synchronization object used to suspend execution until some condition on shared data is met
itk::ConfidenceConnectedImageFilter< TInputImage, TOutputImage >Segment pixels with similar statistics using connectivity
itk::ConformalFlatteningMeshFilter< TInputMesh, TOutputMesh >ConformalFlatteningMeshFilter applies a conformal mapping from 3D to 2D
itk::ConformalMatrixCoefficients< TInputMesh >Compute a matrix filed by Conformal Coefficients of the edge wherever two vertices are connected by an edge
itk::ConicShellInteriorExteriorSpatialFunction< VDimension, TInput >Spatial function implementation of a conic shell
itk::ConjugateGradientOptimizerWrap of the vnl_conjugate_gradient
itk::ConnectedComponentFunctorImageFilter< TInputImage, TOutputImage, TFunctor, TMaskImage >A generic connected components filter that labels the objects in an artibitrary image
itk::ConnectedComponentImageFilter< TInputImage, TOutputImage, TMaskImage >Label the objects in a binary image
itk::ConnectedRegionsMeshFilter< TInputMesh, TOutputMesh >Extract portions of a mesh that are connected at vertices
itk::ConnectedThresholdImageFilter< TInputImage, TOutputImage >Label pixels that are connected to a seed and lie within a range of values
itk::watershed::Segmenter< TInputImage >::connectivity_t
itk::ConstantBoundaryCondition< TImage >This boundary condition returns a constant value for out-of-bounds image pixels
itk::ConstantPadImageFilter< TInputImage, TOutputImage >Increase the image size by padding with a constant value
itk::VectorContainer< TElementIdentifier, TElement >::ConstIterator
itk::Statistics::Histogram< TMeasurement, VMeasurementVectorSize, TFrequencyContainer >::ConstIterator
itk::Statistics::ImageToListAdaptor< TImage, TMeasurementVector >::ConstIterator
itk::Statistics::ListSample< TMeasurementVector >::ConstIterator
itk::Statistics::MembershipSample< TSample >::ConstIterator
itk::Statistics::PointSetToListAdaptor< TPointSet >::ConstIterator
itk::Statistics::Subsample< TSample >::ConstIterator
itk::Statistics::VariableDimensionHistogram< TMeasurement, TFrequencyContainer >::ConstIterator
itk::ConstShapedNeighborhoodIterator< TImage, TBoundaryCondition >::ConstIterator
itk::IndexedContainerInterface< TElementIdentifier, TElement >::ConstIteratorSupport const iteration operations through a container. Dereferencing the iterator must provide an object with the following methods: ElementIdentifier Index(void) const; const Element& Value(void) const;
itk::Statistics::ImageToListSampleAdaptor< TImage >::ConstIterator
itk::Statistics::JointDomainImageToListSampleAdaptor< TImage >::ConstIterator
itk::MapContainer< TElementIdentifier, TElement >::ConstIteratorThe const iterator type for the map
itk::Statistics::PointSetToListSampleAdaptor< TPointSet >::ConstIterator
Histogram::ConstIterator
ListSample::ConstIterator
ListSample::ConstIterator
ListSample::ConstIterator
ListSample::ConstIterator
itk::ConstNeighborhoodIterator< TImage, TBoundaryCondition >Const version of NeighborhoodIterator, defining iteration of a local N-dimensional neighborhood of pixels across an itk::Image
itk::ConstrainedRegionBasedLevelSetFunctionSharedData< TInputImage, TFeatureImage, TSingleData >Helper class used to share data in the ScalarChanAndVeseLevelSetFunction
itk::Functor::ConstrainedValueAddition< TInput1, TInput2, TOutput >
itk::ConstrainedValueAdditionImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements pixel-wise the computation of constrained value addition
itk::Functor::ConstrainedValueDifference< TInput1, TInput2, TOutput >
itk::ConstrainedValueDifferenceImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements pixel-wise the computation of constrained value difference
itk::Concept::DefaultConstructible< T >::Constraints
itk::Concept::CopyConstructible< T >::Constraints
itk::Concept::Convertible< T1, T2 >::Constraints
itk::Concept::LessThanComparable< T1, T2 >::Constraints
itk::Concept::GreaterThanComparable< T1, T2 >::Constraints
itk::Concept::EqualityComparable< T1, T2 >::Constraints
itk::Concept::Assignable< T >::Constraints
itk::Concept::Comparable< T1, T2 >::Constraints
itk::Concept::AdditiveOperators< T1, T2, T3 >::Constraints
itk::Concept::MultiplyOperator< T1, T2, T3 >::Constraints
itk::Concept::MultiplyAndAssignOperator< T1, T2 >::Constraints
itk::Concept::DivisionOperators< T1, T2, T3 >::Constraints
itk::Concept::LogicalOperators< T1, T2, T3 >::Constraints
itk::Concept::BracketOperator< T1, T2, T3 >::Constraints
itk::Concept::NotOperator< T >::Constraints
itk::Concept::IncrementDecrementOperators< T >::Constraints
itk::Concept::OStreamWritable< T >::Constraints
itk::Concept::Signed< T >::Constraints
itk::Concept::SameType< T1, T2 >::Constraints
itk::Concept::HasNumericTraits< T >::Constraints
itk::Concept::SameDimension< D1, D2 >::Constraints
itk::Concept::HasPixelTraits< T >::Constraints
itk::Concept::HasValueType< T >::Constraints
itk::Concept::HasZero< T >::Constraints
itk::Concept::HasJoinTraits< T1, T2 >::Constraints
itk::Concept::SameDimensionOrMinusOne< D1, D2 >::Constraints
itk::Concept::IsInteger< T >::Constraints
itk::Concept::IsFloatingPoint< T >::Constraints
itk::Concept::IsNonInteger< T >::Constraints
itk::Concept::IsFixedPoint< T >::Constraints
itk::FixedArray< TValueType, VLength >::ConstReverseIteratorA const reverse iterator through the array
itk::ConstShapedNeighborhoodIterator< TImage, TBoundaryCondition >Const version of ShapedNeighborhoodIterator, defining iteration of a local N-dimensional neighborhood of pixels across an itk::Image
itk::ConstSliceIterator< TPixel, TContainer >A flexible iterator for itk containers(i.e. itk::Neighborhood) that support pixel access through operator[]
itk::ConstSparseFieldLayerIterator< TNodeType >
itk::ContinuousIndex< TCoordRep, VIndexDimension >A templated class holding a point in n-Dimensional image space
itk::ContourDirectedMeanDistanceImageFilter< TInputImage1, TInputImage2 >Computes the directed Mean distance between the boundaries of non-zero pixel regions of two images
itk::ContourExtractor2DImageFilter< TInputImage >Computes a list of PolyLineParametricPath objects from the contours in a 2D image
itk::ContourMeanDistanceImageFilter< TInputImage1, TInputImage2 >Computes the Mean distance between the boundaries of non-zero regions of two images
itk::ContourSpatialObject< TDimension >Representation of a Contour based on the spatial object classes
itk::ContourSpatialObjectPoint< TPointDimension >Point used for a Contour definition
itk::bio::Gene::ControlDomainType
itk::Concept::Convertible< T1, T2 >
itk::ConvertPixelBuffer< InputPixelType, OutputPixelType, OutputConvertTraits >Class to convert blocks of data from one type to another
itk::ConvolutionImageFilter< TInputImage, TOutputImage >Convolve a given image with an arbitrary image kernel
itk::Functor::CoolColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::Functor::CopperColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::Concept::CopyConstructible< T >
itk::CoreAtomImageToDistanceMatrixProcess< TSourceImage >Computes the distance between all medial nodes (voted core atoms) in a core atom image (input) and stores them in a matrix data object (output)
itk::CoreAtomImageToUnaryCorrespondenceMatrixProcess< TSourceImage >This process takes in two itkBloxCoreAtomImages and runs the itkUnaryMedialNodeMetric on them. It returns a unary correspondence matrix for the images in the form of an itkMatrixResizeableDataObject
itk::CorrelationCoefficientHistogramImageToImageMetric< TFixedImage, TMovingImage >Computes correlation coefficient similarity measure between two images to be registered
itk::CorrespondenceDataStructure< TItemType, VCliqueSize >A data structure designed to contain medial node clique correspondence data between two images
itk::CorrespondenceDataStructureIterator< TStructureType >An iterator designed to easily traverse an itkCorrespondenceDataStructure
itk::CorrespondingList< TItemType, VCliqueSize >Part of the itkCorrespondenceDataStructure
itk::CorrespondingMedialNodeClique< VImageDimension, VCliqueSize >CorrespondingMedialNodeClique is an item stored in CorrespondingNodeList. Specifically it is stored in corresponding node lists and contain pointers to a set of medial nodes (cliques)
itk::Functor::Cos< TInput, TOutput >
itk::CosImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_cos() of its pixels
itk::CosImageFilter< TInputImage, TOutputImage >Computes the vcl_cos(x) pixel-wise
itk::Function::CosineWindowFunction< VRadius, TInput, TOutput >Window function for sinc interpolation.

\[ w(x) = cos(\frac{\pi x}{2 m} ) \]

itk::Accessor::CosPixelAccessor< TInternalType, TExternalType >Give access to the vcl_cos() function of a value
itk::CostFunctionBase class for cost functions intended to be used with Optimizers
itk::Statistics::CovarianceCalculator< TSample >Calculates the covariance matrix of the target sample data
itk::CovarianceImageFunction< TInputImage, TCoordRep >Calculate the covariance matrix in the neighborhood of a pixel in a Vector image
itk::Statistics::CovarianceSampleFilter< TSample >Calculates the covariance matrix of the target sample data
itk::CovariantVector< T, NVectorDimension >A templated class holding a n-Dimensional covariant vector
itk::CoxDeBoorBSplineKernelFunction< VSplineOrder >BSpline kernel used for density estimation and nonparameteric regression
itk::CreateObjectFunction< T >CreateObjectFunction is used to create callback functions that create ITK Objects for use with the itk::ObjectFactory
itk::CreateObjectFunctionBaseDefine API for object creation callback functions
itk::CropImageFilter< TInputImage, TOutputImage >Decrease the image size by cropping the image by an itk::Size at both the upper and lower bounds of the largest possible region
itk::CropLabelMapFilter< TInputImage >Crop a LabelMap image
CrossCompute the cross product of two vectors of dimension 3, independently of the type of the values of vector's elements
itk::CrossHelper< TVector >
itk::CStyleCommandCommand subclass that calls a pointer to a C function
itk::CumulativeGaussianCostFunctionCost function for the Cumulative Gaussian Optimizer
itk::CumulativeGaussianOptimizerThis is an optimizer specific to estimating the parameters of Cumulative Gaussian sampled data
itk::CurvatureAnisotropicDiffusionImageFilter< TInputImage, TOutputImage >
itk::CurvatureFlowFunction< TImage >This class encapsulate the finite difference equation which drives a curvature flow denoising algorithm
itk::CurvatureFlowImageFilter< TInputImage, TOutputImage >Denoise an image using curvature driven flow
itk::CurvatureNDAnisotropicDiffusionFunction< TImage >
itk::CurvesLevelSetFunction< TImageType, TFeatureImageType >This function is used in CurvesLevelSetImageFilter to segment structures in images based on user supplied edge potential map
itk::CurvesLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in images based on user supplied edge potential map
itk::Functor::CustomColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::CylinderSpatialObjectThis class describe a cylinder in 3D only
itk::DanielssonDistanceMapImageFilter< TInputImage, TOutputImage >
itk::DataObjectBase class for all data objects in ITK
itk::DataObjectDecorator< T >Decorates any subclass of itkObject with a DataObject API
itk::DataObjectErrorException object for DataObject exceptions
itk::Statistics::DecisionRuleBase class that allows the setting of usage of different decision rules used in classification This class has the pure virtual function, Evaluate(). Therefore, any subclass should implement the function to be instantiated
itk::DecisionRuleBaseBase class that allows the setting of usage of differnt decision rules used in classification This class has the pure virtual function, Evaluate(). Therefore, any subclass should implement the function to be instantiated
itk::Concept::DefaultConstructible< T >
itk::DefaultConvertPixelTraits< PixelType >Traits class used to by ConvertPixels to convert blocks of pixels
itk::DefaultDynamicMeshTraits< TPixelType, VPointDimension, VMaxTopologicalDimension, TCoordRep, TInterpolationWeight, TCellPixelType >
itk::DefaultImageTraits< TPixelType, VImageDimension, TPixelContainer >Default ImageTraits for any PixelType
itk::DefaultPixelAccessor< TType >Give access to partial aspects a type
itk::DefaultPixelAccessorFunctor< TImageType >This class provides a common API for pixel accessors for Image and VectorImage. (between the DefaultVectorPixelAccessor and DefaultPixelAccessor)
itk::DefaultStaticMeshTraits< TPixelType, VPointDimension, VMaxTopologicalDimension, TCoordRep, TInterpolationWeight, TCellPixelType >
itk::DefaultVectorPixelAccessor< TType >Give access to partial aspects of a type
itk::DefaultVectorPixelAccessorFunctor< TImageType >This class provides a common API for pixel accessors for Image and VectorImage. (between the DefaultVectorPixelAccessor and DefaultPixelAccessor)
DeformableMesh3DThe DeformableMesh3DFilter is used to deform a mesh (deformable model) under a potential force in 2D or 3D. The potential force is derived from the gradient information in the medical image and it will make the model deform to fit to the boundary features
itk::DeformableMesh3DFilter< TInputMesh, TOutputMesh >
itk::DeformableSimplexMesh3DBalloonForceFilter< TInputMesh, TOutputMesh >Additional to its superclass this model adds an balloon force component to the internal forces
itk::DeformableSimplexMesh3DFilter< TInputMesh, TOutputMesh >Three-dimensional deformable model for image segmentation
itk::DeformableSimplexMesh3DGradientConstraintForceFilter< TInputMesh, TOutputMesh >Additional to its superclass this class reimplemets the external forces methos in which the scan line algorithm is used to find highest gradient is found in the direction of the normal to each vertex within a specified range
itk::DeformationFieldJacobianDeterminantFilter< TInputImage, TRealType, TOutputImage >Computes a scalar image from a vector image (e.g., deformation field) input, where each output scalar at each pixel is the Jacobian determinant of the vector field at that location. This calculation is only correct if the the vector field has values that are the absolute locations from which to get the new values are to be taken. This implies that the identity vector field (VF) mapping would have values at each location (x) equal to the location itself. VF(x)=x. THIS IS VERY UNUSUAL. The DeformationFieldJacobianDeterminantFilter computes the proper Jacobian Determinant for a vector field described this way as det[ dT/dx ] = det[ du/dx ]
itk::DeformationFieldSource< TOutputImage >Computes a deformation field from two sets of landmarks
itk::DeleteEvent
itk::DemonsRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >Deformably register two images using the demons algorithm
itk::DemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >
itk::DenseFiniteDifferenceImageFilter< TInputImage, TOutputImage >
itk::Statistics::DenseFrequencyContainerHis class is a container for frequencies of bins in an histogram
itk::Statistics::DenseFrequencyContainer2His class is a container for frequencies of bins in an histogram
itk::Statistics::DensityFunction< TMeasurementVector >DensityFunction class defines common interfaces for density functions
itk::DerivativeImageFilter< TInputImage, TOutputImage >Computes the directional derivative of an image. The directional derivative at each pixel location is computed by convolution with a derivative operator of user-specified order
itk::DerivativeOperator< TPixel, VDimension, TAllocator >A NeighborhoodOperator for taking an n-th order derivative at a pixel
itk::DicomImageIORead DicomImage file format
itk::DICOMImageIO2Read DICOMImage file format
itk::DICOMImageIO2FactoryCreate instances of DICOMImageIO2 objects using an object factory
itk::DicomImageIOFactoryCreate instances of DicomImageIO objects using an object factory
itk::DICOMSeriesFileNamesGenerate an ordered sequence of filenames
itk::DiffeomorphicDemonsRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >Deformably register two images using a diffeomorphic demons algorithm
itk::DifferenceImageFilter< TInputImage, TOutputImage >Implements comparison between two images
itk::DifferenceOfGaussiansGradientImageFilter< TInputImage, TDataType >Performs difference-of-gaussians gradient detection
itk::DiffusionTensor3D< TComponent >Represent a diffusion tensor as used in DTI images
itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >This class takes as input one or more reference image (acquired in the absence of diffusion sensitizing gradients) and 'n' diffusion weighted images and their gradient directions and computes an image of tensors. (with DiffusionTensor3D as the pixel type). Once that is done, you can apply filters on this tensor image to compute FA, ADC, RGB weighted maps etc
itk::DilateObjectMorphologyImageFilter< TInputImage, TOutputImage, TKernel >Dilation of an object in an image
itk::DirectedHausdorffDistanceImageFilter< TInputImage1, TInputImage2 >Computes the directed Hausdorff distance between the set of non-zero pixels of two images
itk::DirectFourierReconstructionImageToImageFilter< TInputPixelType, TOutputPixelType >Direct fourier reconstruction filter of a tomographic volume
itk::DirectoryPortable directory/filename traversal
itk::DiscreteGaussianDerivativeImageFilter< TInputImage, TOutputImage >Calculates image derivatives using discrete derivative gaussian kernels. This filter calculates Gaussian derivative by separable convolution of an image and a discrete Gaussian derivative operator (kernel)
itk::DiscreteGaussianDerivativeImageFunction< TInputImage, TOutput >Compute the discrete gaussian derivatives of an the image at a specific location in space, i.e. point, index or continuous index. This class computes a single derivative given the order in each direction (by default zero). This class is templated over the input image type
itk::DiscreteGaussianImageFilter< TInputImage, TOutputImage >Blurs an image by separable convolution with discrete gaussian kernels. This filter performs Gaussian blurring by separable convolution of an image and a discrete Gaussian operator (kernel)
itk::DiscreteGradientMagnitudeGaussianImageFunction< TInputImage, TOutput >Compute the discrete gradient magnitude gaussian of an the image at a specific location in space, i.e. point, index or continuous index. This class computes a single derivative given the order in each direction (by default zero). This class is templated over the input image type
itk::DiscreteHessianGaussianImageFunction< TInputImage, TOutput >Compute the Hessian Gaussian of an image at a specific location in space by calculating discrete second-order gaussian derivatives. This class is templated over the input image type
itk::ImageToImageFilterDetail::DispatchBaseBase class for a class used to dispatch to dimension specific implementations
itk::DisplacementFieldJacobianDeterminantFilter< TInputImage, TRealType, TOutputImage >Computes a scalar image from a vector image (e.g., deformation field) input, where each output scalar at each pixel is the Jacobian determinant of the vector field at that location. This calculation is correct in the case where the vector image is a "displacement" from the current location. The computation for the jacobian determinant is: det[ dT/dx ] = det[ I + du/dx ]
itk::Statistics::DistanceMetric< TVector >This class declares common interfaces for distance functions
itk::Statistics::DistanceToCentroidMembershipFunction< TVector >Class represents DistanceToCentroid Density Function
itk::Function::Div< TInput1, TInput2, TOutput >
itk::Functor::DivideByConstant< TInput, TConstant, TOutput >
itk::DivideByConstantImageFilter< TInputImage, TConstant, TOutputImage >Divide input pixels by a constant
itk::DivideImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements an operator for pixel-wise division of two images
itk::Concept::DivisionOperators< T1, T2, T3 >
itk::DoubleThresholdImageFilter< TInputImage, TOutputImage >Binarize an input image using double thresholding
itk::DTITubeSpatialObject< TDimension >Representation of a tube based on the spatial object classes
itk::DTITubeSpatialObjectPoint< TPointDimension >Point used for a tube definition
itk::DynamicLoaderPortable loading of dynamic libraries or dll's
itk::watershed::SegmentTable< TScalarType >::edge_pair_t
itk::Functor::EdgePotential< TInput, TOutput >
itk::EdgePotentialImageFilter< TInputImage, TOutputImage >Computes the edge potential of an image from the image gradient
itk::EigenAnalysis2DImageFilter< TInputImage, TEigenValueImage, TEigenVectorImage >Computes pixel-wise the eigen values and eigen vectors of a 2D symmetrical matrix
itk::ElasticBodyReciprocalSplineKernelTransform< TScalarType, NDimensions >
itk::ElasticBodySplineKernelTransform< TScalarType, NDimensions >This class defines the elastic body spline (EBS) transformation
itk::fem::ElementAbstract base element class
itk::fem::Element1DStress< TBaseClass >Class that is used to define linear elasticity problem in 1D space
itk::fem::Element2DC0LinearLine2-noded, linear, C0 continuous line element in 2D space
itk::fem::Element2DC0LinearLineStress2-noded finite element class in 2D space for linear elasticity problem
itk::fem::Element2DC0LinearQuadrilateral4-noded, linear, C0 continuous finite element in 2D space
itk::fem::Element2DC0LinearQuadrilateralMembrane4-noded finite element class in 2D space for linear elasticity problem
itk::fem::Element2DC0LinearQuadrilateralStrain4-noded finite element class in 2D space for linear elasticity problem
itk::fem::Element2DC0LinearQuadrilateralStress4-noded finite element class in 2D space for linear elasticity problem
itk::fem::Element2DC0LinearTriangular3-noded, linear, C0 continuous finite element in 2D space
itk::fem::Element2DC0LinearTriangularMembrane3-noded finite element class in 2D space for linear elasticity problem
itk::fem::Element2DC0LinearTriangularStrain3-noded finite element class in 2D space for linear elasticity problem
itk::fem::Element2DC0LinearTriangularStress3-noded finite element class in 2D space for linear elasticity problem
itk::fem::Element2DC0QuadraticTriangular3-noded, quadratic, C0 continuous finite element in 2D space
itk::fem::Element2DC0QuadraticTriangularStrain3-noded finite element class in 2D space for linear elasticity problem
itk::fem::Element2DC0QuadraticTriangularStress3-noded finite element class in 2D space for linear elasticity problem
itk::fem::Element2DC1Beam1D Beam (spring that also bends) finite element in 2D space
itk::fem::Element2DMembrane< TBaseClass >Class that is used to define a membrane energy problem in 2D space
itk::fem::Element2DStrain< TBaseClass >Class that is used to define linear elasticity problem in 2D space
itk::fem::Element2DStress< TBaseClass >Class that is used to define linear elasticity problem in 2D space
itk::fem::Element3DC0LinearHexahedron8-noded, linear, C0 continuous finite element in 3D space
itk::fem::Element3DC0LinearHexahedronMembrane8-noded finite element class in 3D space for linear elasticity problem
itk::fem::Element3DC0LinearHexahedronStrain8-noded finite element class in 3D space for linear elasticity problem
itk::fem::Element3DC0LinearTetrahedron4-noded, linear, C0 continuous finite element in 3D space
itk::fem::Element3DC0LinearTetrahedronMembrane4-noded finite element class in 3D space for linear elasticity problem
itk::fem::Element3DC0LinearTetrahedronStrain4-noded finite element class in 3D space for linear elasticity problem
itk::fem::Element3DMembrane< TBaseClass >Class that is used to define a membrane energy problem in 3D space
itk::fem::Element3DStrain< TBaseClass >Class that is used to define linear elasticity problem in 3D space
itk::fem::ElementStd< VNumberOfNodes, VNumberOfSpatialDimensions, TBaseClass >Implements standard node management in the element classes
itk::ElementWrapperInterface< TElement, TElementIdentifier >
itk::ElementWrapperPointerInterface< TElementWrapperPointer, TElementIdentifier >
itk::EllipseSpatialObject< TDimension >TODO
itk::EllipsoidInteriorExteriorSpatialFunction< VDimension, TInput >
EllipsoidSpatialFunctionFunction implementation of an ellipsoid
EllipsoidSpatialFunctionFunction implementation of an ellipsoid
itk::Functor::ElongationLabelObjectAccessor< TLabelObject >
itk::EndEvent
itk::EndPickEvent
itk::Concept::EqualityComparable< T1, T2 >
itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >
itk::EquivalencyTableHash table to manage integral label equivalencies
itk::Functor::EquivalentEllipsoidSizeLabelObjectAccessor< TLabelObject >
itk::Functor::EquivalentPerimeterLabelObjectAccessor< TLabelObject >
itk::Functor::EquivalentRadiusLabelObjectAccessor< TLabelObject >
itk::ErodeObjectMorphologyImageFilter< TInputImage, TOutputImage, TKernel >Erosion of an object in an image
itk::Statistics::ErrorBackPropagationLearningFunctionBase< LayerType, TTargetVector >
ErrorBackPropagationLearningFunctionBaseThe ErrorBackPropagationLearningFunctionBase is the base class for all the ErrorBackPropagationLearning strategies. These include error back propagation, bp+momentum, conjugte gradient descent, quick prop. This class specifies how the errors are backpropagated for a layer. They take a LayerBase object as input and compute the input for the layers input weightset
itk::Statistics::ErrorBackPropagationLearningWithMomentum< LayerType, TTargetVector >
ErrorBackPropagationLearningWithMomentumThe ErrorBackPropagationLearningWithMomentum is the base class for all the ErrorBackPropagationLearning strategies. These include error back propagation, bp+momentum, conjugte gradient descent, quick prop. This class specifies how the errors are backpropagated for a layer. They take a LayerBase object as input and compute the input for the layers input weightset
itk::Statistics::ErrorFunctionBase< TMeasurementVector, TTargetVector >
itk::ESMDemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >Fast implementation of the symmetric demons registration force
itk::Statistics::EuclideanDistance< TVector >Euclidean distance function
itk::Statistics::EuclideanDistanceMetric< TVector >Euclidean distance function
itk::EuclideanDistancePointMetric< TFixedPointSet, TMovingPointSet, TDistanceMap >Computes the minimum distance between a moving point-set and a fixed point-set. A vector of minimum closest point distance is created for each point in the moving point-set. No correspondance is needed. For speed consideration, the point-set with the minimum number of points should be used as the moving point-set. If the number of points is high, the possibility of setting a distance map should improve the speed of the closest point computation
itk::Statistics::EuclideanSquareDistanceMetric< TVector >Computes Euclidean distance between origin and given measurement vector
itk::Euler2DTransform< TScalarType >Euler2DTransform of a vector space (e.g. space coordinates)
itk::Euler3DTransform< TScalarType >Euler3DTransform of a vector space (e.g. space coordinates)
EulerOperatorCreateCenterVertexFunctionCreate a vertex at the barycenter of the given face
EulerOperatorDeleteCenterVertexFunctionDelete the vertex, connected edges and faces and create a new face In place of the previous vertex' one-ring
EulerOperatorFlipEdgeFunctionFlip an edge
EulerOperatorJoinFacetFunctionJoin the two facets which are on both sides of a given internal edge
EulerOperatorJoinVertexFunctionCollapse a given edge by joining its dest and its org
EulerOperatorSplitEdgeFunctionGiven Edge is splitted into two and associated faces see their degree increased by one (a triangle is transformed into a quad for example)
EulerOperatorSplitFacetFunctionGiven two edges h and g sharing the same Left() face, create a new edge joining h->Destination() to g->Destination(), thus splitting the original Left()
EulerOperatorSplitVertexFunctionFor two given edges e and f sharing the same dest(), disconnect the two rings, create a new point to be set at f->dest(), and create a new edge between e->Destination() and f->Destination()
itk::EventObjectAbstraction of the Events used to communicating among filters and with GUIs
itk::ExhaustiveOptimizerOptimizer that fully samples a grid on the parametric space
itk::ExitEvent
itk::Function::Exp< TInput, TOutput >
itk::ExpandImageFilter< TInputImage, TOutputImage >Expand the size of an image by an integer factor in each dimension
itk::Statistics::ExpectationMaximizationMixtureModelEstimator< TSample >This class generates the parameter estimates for a mixture model using expectation maximization strategy
itk::ExpImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_exp() of its pixels
itk::ExpImageFilter< TInputImage, TOutputImage >Computes the vcl_exp(x) pixel-wise
itk::Function::ExpNegative< TInput, TOutput >
itk::ExpNegativeImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_exp() of its pixels
itk::ExpNegativeImageFilter< TInputImage, TOutputImage >Computes the function vcl_exp(-K.x) pixel-wise
itk::Accessor::ExpNegativePixelAccessor< TInternalType, TExternalType >Give access to the vcl_exp() function of a value
itk::ExponentialDeformationFieldImageFilter< TInputImage, TOutputImage >Computes a diffeomorphic deformation field as the Lie group exponential of a vector field
itk::Accessor::ExpPixelAccessor< TInternalType, TExternalType >Give access to the vcl_exp() function of a value
itk::ExtensionVelocitiesImageFilter< TLevelSet, TAuxValue, VAuxDimension >Extend velocities smoothly from a particular level set
itk::ExtractImageFilter< TInputImage, TOutputImage >Decrease the image size by cropping the image to the selected region bounds
itk::ImageToImageFilterDetail::ExtractImageFilterRegionCopier< T1, T2 >
itk::ExtractOrthogonalSwath2DImageFilter< TImage >Extracts into rectangular form a "swath" image from the input image along the parametric path
itk::ExtrapolateImageFunction< TInputImage, TCoordRep >Base class for all image extrapolaters
itk::watershed::Boundary< TScalarType, TDimension >::face_pixel_t
itk::FastApproximateRankImageFilter< TInputImage, TOutputImage >A separable rank filter
itk::FastChamferDistanceImageFilter< TInputImage, TOutputImage >This class compute the signed (positive and negative) chamfer distance in a narrow band
itk::FastIncrementalBinaryDilateImageFilter< TInputImage, TOutputImage, TKernel >Fast binary dilation
itk::FastMarchingExtensionImageFilter< TLevelSet, TAuxValue, VAuxDimension, TSpeedImage >Extend auxiliary variables smoothly using Fast Marching
itk::FastMarchingImageFilter< TLevelSet, TSpeedImage >Solve an Eikonal equation using Fast Marching
itk::FastMarchingUpwindGradientImageFilter< TLevelSet, TSpeedImage >Generates the upwind gradient field of fast marching arrival times
itk::FastMutexLockCritical section locking class
itk::FastSymmetricForcesDemonsRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >Deformably register two images using a symmetric forces demons algorithm
itk::FastSymmetricForcesDemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >
itk::FiniteDifferenceSparseImageFilter< TInputImageType, TSparseOutputImageType >::FDThreadStruct
itk::MRCHeaderObject::FeiExtendedHeader
itk::fem::FEMExceptionBase class for all exception's that can occur within FEM classes
itk::fem::FEMExceptionIOBase class for all IO exception's that can occur within FEM classe
itk::fem::FEMExceptionItpackSolverHandles errors that occur in itpack solving routines
itk::fem::FEMExceptionItpackSparseMatrixSbagnHandles errors that occur when unfinalizing the matrix
itk::fem::FEMExceptionItpackSparseMatrixSbsijHandles errors that occur when building the matrix
itk::fem::FEMExceptionLinearSystem
itk::fem::FEMExceptionLinearSystemBounds
itk::fem::FEMExceptionObjectNotFoundObject not found exception
itk::fem::FEMExceptionSolutionBase class for all exceptions that can occur when solving FEM problem
itk::fem::FEMExceptionWrongClassBad object exception
itk::fem::FEMInitializationFEM Library initialization and housekeeping
itk::fem::FEMLightObjectBase class for all classes that define the FEM system
itk::fem::FEMObjectFactory< T >Create objects of derived classes by specifying a class ID
itk::fem::FEMRegistrationFilter< TMovingImage, TFixedImage >::FEMOF
itk::fem::FEMP< T >Pointer used to store polymorphic elements in STL arrays
itk::fem::FEMPArray< T >Array for FEMP objects
itk::fem::FEMRegistrationFilter< TMovingImage, TFixedImage >FEM Image registration filter. The image registration problem is modeled here with the finite element method. Image registration is, in general, an ill-posed problem. Thus, we use an optimization scheme where the optimization criterion is given by a regularized variational energy. The variational energy arises from modeling the image as a physical body on which external forces act. The body is allowed to deform so as to minimize the applied force. The resistance of the physical body to deformation, determined by the physics associated with the body, serves to regularize the solution. The forces applied to the body are, generally, highly non-linear and so the body is allowed to deform slowly and incrementally. The direction it deforms follows the gradient of the potential energy (the force) we define. The potential energies we may choose from are given by the itk image-to-image metrics. The choices and the associated direction of descent are : Mean Squares (minimize), Normalized Cross-Correlation (maximize) Mutual Information (maximize). Note that we have to set the direction (SetDescentDirection) when we choose a metric. The forces driving the problem may also be given by user-supplied landmarks. The corners of the image, in this example, are always pinned. This example is designed for 2D or 3D images. A rectilinear mesh is generated automatically given the correct element type (Quadrilateral or Hexahedral). Our specific Solver for this example uses trapezoidal time stepping. This is a method for solving a second-order PDE in time. The solution is penalized by the zeroth (mass matrix) and first derivatives (stiffness matrix) of the shape functions. There is an option to perform a line search on the energy after each iteration. Optimal parameter settings require experimentation. The following approach tends to work well : Choose the relative size of density to elasticity (e.g. Rho / E ~= 1.) such that the image deforms locally and slowly. This also affects the stability of the solution. Choose the time step to control the size of the deformation at each step. Choose enough iterations to allow the solution to converge (this may be automated)
itk::Functor::FeretDiameterLabelObjectAccessor< TLabelObject >
itk::FFTComplexConjugateToRealImageFilter< TPixel, VDimension >TODO
itk::FFTComplexToComplexImageFilter< TPixel, NDimension >Implements an API to enable the Fourier transform or the inverse Fourier transform of images with complex valued voxels to be computed
itk::FFTRealToComplexConjugateImageFilter< TPixel, VDimension >TODO
itk::FFTShiftImageFilter< TInputImage, TOutputImage >Shift the zero-frequency components to center of the image
itk::FFTWComplexConjugateToRealImageFilter< TPixel, VDimension >
itk::FFTWRealToComplexConjugateImageFilter< TPixel, VDimension >
itk::FileOutputWindowMessages sent from the system are sent to a file
itk::FiniteCylinderSpatialFunction< VDimension, TInput >Function implementation of an finite cylinder
itk::FiniteDifferenceFunction< TImageType >
itk::fem::FiniteDifferenceFunctionLoad< TMoving, TFixed >General image pair load that uses the itkFiniteDifferenceFunctions
itk::FiniteDifferenceImageFilter< TInputImage, TOutputImage >
itk::FiniteDifferenceSparseImageFilter< TInputImageType, TSparseOutputImageType >This class implements a multi-threaded base class for Image to SparseImage finite difference processes
itk::FiniteDifferenceSparseImageFunction< TSparseImageType >This is the base class for function classes that can be used with filters derived from FiniteDifferenceSparseImageFilter
itk::FixedArray< TValueType, VLength >Simulate a standard C array with copy semnatics
itk::FixedCenterOfRotationAffineTransform< TScalarType, NDimensions >Affine transformation with a specified center of rotation
FixedImageSamplePoint
FixedImageSpatialSample
itk::watershed::Boundary< TScalarType, TDimension >::flat_region_t
itk::watershed::Segmenter< TInputImage >::flat_region_t
itk::Functor::FlatnessLabelObjectAccessor< TLabelObject >
itk::FlatStructuringElement< VDimension >A class to support a variety of flat structuring elements, including versions created by decomposition of lines
itk::FlipImageFilter< TImage >Flips an image across user specified axes
itk::FloodFilledFunctionConditionalConstIterator< TImage, TFunction >Iterates over a flood-filled spatial function
itk::FloodFilledImageFunctionConditionalConstIterator< TImage, TFunction >Iterates over a flood-filled image function
itk::FloodFilledImageFunctionConditionalIterator< TImage, TFunction >Iterates over a flood-filled image function
itk::FloodFilledSpatialFunctionConditionalConstIterator< TImage, TFunction >Iterates over a flood-filled spatial function
itk::FloodFilledSpatialFunctionConditionalIterator< TImage, TFunction >Iterates over a flood-filled spatial function
itk::ForwardDifferenceOperator< TPixel, VDimension, TAllocator >Operator whose inner product with a neighborhood returns a "half" derivative at the center of the neighborhood
itk::FourierSeriesPath< VDimension >Represent a closed path through ND Space by its frequency components
itk::QuadEdgeMeshFrontBaseIterator< TMesh, TQE >::FrontAtomAtomic information associated to each edge of the front
itk::FRPROptimizerImplements Fletch-Reeves & Polak-Ribiere optimization using dBrent line search
itk::FrustumSpatialFunction< VImageDimension, TInput >Spatial function implementation of a truncated pyramid
itk::FunctionAndGradientEvaluationIterationEvent
itk::FunctionBase< TInput, TOutput >Base class for all ITK function objects
itk::FunctionEvaluationIterationEvent
itk::GaborImageSource< TOutputImage >Generate an n-dimensional image of a Gabor filter
itk::GaborKernelFunctionGabor kernel used for various computer vision tasks
itk::GaussianBlurImageFunction< TInputImage, TOutput >Compute the convolution of a neighborhood operator with the image at a specific location in space, i.e. point, index or continuous index. This class is templated over the input image type
itk::Statistics::GaussianDensityFunction< TMeasurementVector >GaussianDensityFunction class represents Gaussian Density Function
itk::GaussianDerivativeImageFunction< TInputImage, TOutput >Compute the gaussian derivatives of an the image at a specific location in space, i.e. point, index or continuous index. This class is templated over the input image type
itk::GaussianDerivativeOperator< TPixel, VDimension, TAllocator >A NeighborhoodOperator whose coefficients are a one dimensional, discrete derivative Gaussian kernel
itk::GaussianDerivativeSpatialFunction< TOutput, VImageDimension, TInput >N-dimensional gaussian spatial function class
itk::Statistics::GaussianDistributionGaussianDistribution class defines the interface for a univariate Gaussian distribution (pdfs, cdfs, etc.)
itk::Statistics::GaussianGoodnessOfFitComponent< TInputSample >GoodnessOfFitComponent for Gaussian distribution
itk::GaussianImageSource< TOutputImage >Generate an n-dimensional image of a Gaussian
itk::GaussianKernelFunctionGaussian kernel used for density estimation and nonparameteric regression
itk::Statistics::GaussianMembershipFunction< TMeasurementVector >GaussianMembershipFunction class represents Gaussian function
itk::Statistics::GaussianMixtureModelComponent< TSample >Component (derived from MixtureModelComponentBase) for Gaussian class. This class is used in ExpectationMaximizationMixtureModelEstimator
itk::GaussianOperator< TPixel, VDimension, TAllocator >A NeighborhoodOperator whose coefficients are a one dimensional, discrete Gaussian kernel
itk::Statistics::GaussianRadialBasisFunction< ScalarType >
itk::GaussianSpatialFunction< TOutput, VImageDimension, TInput >N-dimensional gaussian spatial function class
itk::GaussianSpatialObject< TDimension >Represents a multivariate Gaussian function
itk::Statistics::GaussianTransferFunction< ScalarType >
itk::fem::GaussIntegrateUse the Gauss-Legendre formula to perform integration
itk::GDCMImageIOImageIO class for reading and writing DICOM V3.0 and ACR/NEMA 1&2 uncompressed images This class is only an adaptor to the gdcm library (currently gdcm 1.2.x is used by default):
itk::GDCMImageIOFactoryCreate instances of GDCMImageIO objects using an object factory
itk::GDCMSeriesFileNamesGenerate a sequence of filenames from a DICOM series
itk::GE4ImageIOClass that defines how to read GE4 file format
itk::GE4ImageIOFactoryCreate instances of GE4ImageIO objects using an object factory
itk::GE5ImageIOClass that defines how to read GE5 file format
itk::GE5ImageIOFactoryCreate instances of GE5ImageIO objects using an object factory
itk::GEAdwImageIOClass that defines how to read GEAdw file format
itk::GEAdwImageIOFactoryCreate instances of GEAdwImageIO objects using an object factory
GEImageHeader
itk::bio::GeneThis class implement the abstraction of a biological gene
itk::bio::GeneNetworkThis class implement the abstraction of a biological gene network
itk::bio::GenomeThis class implement the abstraction of a biological genome
itk::GeodesicActiveContourLevelSetFunction< TImageType, TFeatureImageType >This function is used in GeodesicActiveContourLevelSetImageFilter to segment structures in an image based on a user supplied edge potential map
itk::GeodesicActiveContourLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in images based on a user supplied edge potential map
itk::GeodesicActiveContourShapePriorLevelSetFunction< TImageType, TFeatureImageType >This function is used in GeodesicActiveContourShapePriorSegmentationLevelSetFilter to segment structures in an image based on user supplied edge potential map and shape model
itk::GeodesicActiveContourShapePriorLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in an image based on a user supplied edge potential map and user supplied shape model
itk::GeometricalQuadEdge< TVRef, TFRef, TPrimalData, TDualData, PrimalDual >This class extends the QuadEdge by adding a reference to the Origin
itk::Statistics::GetAdaptorMeasurementVectorLength< TAdaptor >
itk::GetAverageSliceImageFilter< TInputImage, TOutputImage >Averages a single dimension of an image
itk::GetDimension< T >
itk::Statistics::GetHistogramDimension< THistogram >
itk::GetImageDimension< TImage >
itk::GetMeshDimension< TMesh >
itk::GetPointSetDimension< TPointSet >
itk::GetVectorDimension< TVector >
itk::GiplImageIORead GiplImage file format
itk::GiplImageIOFactoryCreate instances of GiplImageIO objects using an object factory
itk::NCCRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct
itk::SymmetricForcesDemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct
itk::DemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct
itk::LevelSetMotionRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct
itk::ESMDemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct
itk::MeanSquareRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct
itk::FastSymmetricForcesDemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct
itk::RegionBasedLevelSetFunction< TInput, TFeature, TSharedData >::GlobalDataStruct
itk::MIRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct
itk::LevelSetFunction< TImageType >::GlobalDataStruct
itk::Statistics::GoodnessOfFitComponentBase< TInputSample >Component (module) type specific functionalities for GoodnessOfFitMixtureModelCostFunction
itk::Statistics::GoodnessOfFitFunctionBase< TInputHistogram >Base class for classes calculates different types of goodness-of-fit statistics
itk::Statistics::GoodnessOfFitMixtureModelCostFunction< TInputSample >Calculates the goodness-of-fit statstics for multivarate mixture model
itk::GradientAnisotropicDiffusionImageFilter< TInputImage, TOutputImage >
itk::GradientDescentOptimizerImplement a gradient descent optimizer
itk::GradientDifferenceImageToImageMetric< TFixedImage, TMovingImage >Computes similarity between two objects to be registered
itk::GradientEvaluationIterationEvent
itk::GradientImageFilter< TInputImage, TOperatorValueType, TOutputValueType >Computes the gradient of an image using directional derivatives
itk::GradientImageToBloxBoundaryPointImageFilter< TInputImage >Converts a gradient image to an BloxImage of BloxBoundaryPoints
itk::Functor::GradientMagnitude< TInput, TOutput >
itk::GradientMagnitudeImageFilter< TInputImage, TOutputImage >Computes the gradient magnitude of an image region at each pixel
itk::GradientMagnitudeRecursiveGaussianImageFilter< TInputImage, TOutputImage >Computes the Magnitude of the Gradient of an image by convolution with the first derivative of a Gaussian
itk::GradientNDAnisotropicDiffusionFunction< TImage >
itk::GradientRecursiveGaussianImageFilter< TInputImage, TOutputImage >Computes the gradient of an image by convolution with the first derivative of a Gaussian
itk::GradientToMagnitudeImageFilter< TInputImage, TOutputImage >Take an image of vectors as input and produce an image with the magnitude of those vectors
itk::GradientVectorFlowImageFilter< TInputImage, TOutputImage, TInternalPixel >This class computes a diffusion of the gradient vectors for graylevel or binary edge map derive from the image. It enlarges the capture range of the gradient force and make external force derived from the gradient work effectively in the framework of deformable model
itk::GrayscaleConnectedClosingImageFilter< TInputImage, TOutputImage >Enhance pixels associated with a dark object (identified by a seed pixel) where the dark object is surrounded by a brigher object
itk::GrayscaleConnectedOpeningImageFilter< TInputImage, TOutputImage >Enhance pixels associated with a bright object (identified by a seed pixel) where the bright object is surrounded by a darker object
itk::GrayscaleDilateImageFilter< TInputImage, TOutputImage, TKernel >Gray scale dilation of an image
itk::GrayscaleErodeImageFilter< TInputImage, TOutputImage, TKernel >Gray scale erosion of an image
itk::GrayscaleFillholeImageFilter< TInputImage, TOutputImage >Remove local minima not connected to the boundary of the image
itk::GrayscaleFunctionDilateImageFilter< TInputImage, TOutputImage, TKernel >Gray scale function dilation of an image
itk::GrayscaleFunctionErodeImageFilter< TInputImage, TOutputImage, TKernel >Gray scale function erosion of an image
itk::GrayscaleGeodesicDilateImageFilter< TInputImage, TOutputImage >Geodesic gray scale dilation of an image
itk::GrayscaleGeodesicErodeImageFilter< TInputImage, TOutputImage >Geodesic gray scale erosion of an image
itk::GrayscaleGrindPeakImageFilter< TInputImage, TOutputImage >Remove local maxima not connected to the boundary of the image
itk::GrayscaleMorphologicalClosingImageFilter< TInputImage, TOutputImage, TKernel >Gray scale morphological closing of an image
itk::GrayscaleMorphologicalOpeningImageFilter< TInputImage, TOutputImage, TKernel >Gray scale morphological opening of an image
itk::Concept::GreaterThanComparable< T1, T2 >
itk::Functor::GreenColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::GreenPixelAccessor< T >Give access to the Green component of a RGBPixel type
itk::Functor::GreyColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::Statistics::GreyLevelCooccurrenceMatrixTextureCoefficientsCalculator< THistogram >This class computes texture feature coefficients from a grey level co-occurrence matrix
itk::GridForwardWarpImageFilter< TDeformationField, TOutputImage >Warps a grid using an input deformation field
itk::GridImageSource< TOutputImage >Generate an n-dimensional image of a grid
itk::GroupSpatialObject< TDimension >Representation of a group based on the spatial object classes
itk::Function::HammingWindowFunction< VRadius, TInput, TOutput >Window function for sinc interpolation.

\[ w(x) = 0.54 + 0.46 cos(\frac{\pi x}{m} ) \]

itk::Statistics::HardLimitTransferFunction< ScalarType >
itk::HarmonicMatrixCoefficients< TInputMesh >Compute a matrix filled with Harmonic coefficients, wherever two vertices are connected by an edge
itk::hash< Key >
itk::hash< char * >
itk::hash< char >
itk::hash< const char * >
itk::hash< int >
itk::hash< long >
itk::hash< short >
itk::hash< signed char >
itk::hash< unsigned char >
itk::hash< unsigned int >
itk::hash< unsigned long >
itk::hash< unsigned short >
itk::hash_map< Key, T,,, >Replacement for STL hash map because some systems do not support it, or support it incorrectly
itk::hash_multimap< Key, T,,, >
itk::hash_multiset< Value,,, >
itk::hash_set< Value,,, >Replacement for STL hash set because some systems do not support it, or support it incorrectly
itk::hashtable< Value, Key, HashFcn, ExtractKey, EqualKey, Alloc >
itk::hashtable_base< Value, Alloc >
itk::hashtable_const_iterator< Value, Key, HashFcn, ExtractKey, EqualKey, Alloc >
itk::hashtable_iterator< Value, Key, HashFcn, ExtractKey, EqualKey, Alloc >
itk::hashtable_node< Value >
itk::Concept::HasJoinTraits< T1, T2 >
itk::Concept::HasNumericTraits< T >
itk::Concept::HasPixelTraits< T >
itk::Concept::HasValueType< T >
itk::Concept::HasZero< T >
itk::HausdorffDistanceImageFilter< TInputImage1, TInputImage2 >Computes the Hausdorff distance between the set of non-zero pixels of two images
itk::HConcaveImageFilter< TInputImage, TOutputImage >Identify local minima whose depth below the baseline is greater than h
itk::HConvexImageFilter< TInputImage, TOutputImage >Identify local maxima whose height above the baseline is greater than h
itk::MRCHeaderObject::Header
itk::HeavisideStepFunction< TInput, TOutput >Implementation of the classical Heaviside step function
itk::HeavisideStepFunctionBase< TInput, TOutput >Base class of the Heaviside function
itk::Hessian3DToVesselnessMeasureImageFilter< TPixel >Line filter to provide a vesselness measure for tubular objects from the hessian matrix. The filter takes as input an image of hessian pixels (SymmetricSecondRankTensor pixels) and preserves pixels that have eigen values $ \lambda_3 $ close to 0 and $\lambda_2$ and $\lambda_1$ as large negative values. (for bright tubular structures)
itk::HessianRecursiveGaussianImageFilter< TInputImage, TOutputImage >Computes the Hessian matrix of an image by convolution with the Second and Cross derivatives of a Gaussian
itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >A filter to enhance M-dimensional objects in N-dimensional images
itk::HexahedronCell< TCellInterface >
itk::HexahedronCellTopology
itk::Statistics::Histogram< TMeasurement, VMeasurementVectorSize, TFrequencyContainer >This class stores measurement vectors in the context of n-dimensional histogram
itk::HistogramAlgorithmBase< TInputHistogram >Base class for algorithms operating on histograms
itk::Function::HistogramEntropyFunction< TInput, TOutput >
itk::HistogramImageToImageMetric< TFixedImage, TMovingImage >Computes similarity between two objects to be registered
itk::Function::HistogramIntensityFunction< TInput, TOutput >
itk::Functor::HistogramLabelObjectAccessor< TLabelObject >
itk::Function::HistogramLogProbabilityFunction< TInput, TOutput >
itk::HistogramMatchingImageFilter< TInputImage, TOutputImage, THistogramMeasurement >Normalize the grayscale values between two image by histogram matching
itk::Function::HistogramProbabilityFunction< TInput, TOutput >
itk::HistogramToEntropyImageFilter< THistogram, TOutputPixel >The class takes a histogram as an input and gives the entropy image as the output. A pixel, at position I, in the output image is given by
itk::HistogramToImageFilter< THistogram, TFunction >This class takes a histogram as an input and returns an image of type specified by the functor
itk::HistogramToIntensityImageFilter< THistogram, TOutputPixel >The class takes a histogram as an input and produces an image as the output. A pixel, at position I, in the output image is given by
itk::HistogramToLogProbabilityImageFilter< THistogram, TOutputPixel >The class takes a histogram as an input and gives the log probability image as the output. A pixel, at position I, in the output image is given by
itk::HistogramToProbabilityImageFilter< THistogram, TOutputPixel >The class takes a histogram as an input and gives the probability image as the output. A pixel, at position I, in the output image is given by
itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >This class computes texture feature coefficients from a grey level co-occurrence matrix
itk::HMaximaImageFilter< TInputImage, TOutputImage >Suppress local maxima whose height above the baseline is less than h
itk::HMinimaImageFilter< TInputImage, TOutputImage >Suppress local minima whose depth below the baseline is less than h
itk::Functor::HotColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::HoughTransform2DCirclesImageFilter< TInputPixelType, TOutputPixelType >Performs the Hough Transform to find circles in a 2D image
itk::HoughTransform2DLinesImageFilter< TInputPixelType, TOutputPixelType >Performs the Hough Transform to find 2D straight lines in a 2D image
itk::Functor::HSVColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::Statistics::HypersphereKernelMeanShiftModeSeeker< TSample >Evolves the mode using a hyperspherical kernel defined by a radius (which is set by SetRadius) method
itk::AutomaticTopologyMeshSource< TOutputMesh >::IdentifierArrayEqualsFunction
itk::AutomaticTopologyMeshSource< TOutputMesh >::IdentifierArrayHashFunction
itk::Statistics::IdentityTransferFunction< ScalarType >
itk::IdentityTransform< TScalarType, NDimensions >Implementation of an Identity Transform
itk::Image< TPixel, VImageDimension >Templated n-dimensional image class
itk::ImageAdaptor< TImage, TAccessor >Give access to partial aspects of voxels from an Image
itk::ImageAndPathToImageFilter< TInputImage, TInputPath, TOutputImage >Base class for filters that take both a path and an image as input and produce a path as output
itk::ImageBase< VImageDimension >Base class for templated image classes
itk::ImageBoundaryCondition< TImageType >A virtual base object that defines an interface to a class of boundary condition objects for use by neighborhood iterators
itk::NeighborhoodAlgorithm::ImageBoundaryFacesCalculator< TImage >
itk::ImageClassifierBase< TInputImage, TClassifiedImage >Base class for ImageClassifierBase object
itk::Statistics::ImageClassifierFilter< TSample, TInputImage, TOutputImage >Image classification class
itk::ImageConstIterator< TImage >A multi-dimensional image iterator templated over image type
itk::ImageConstIteratorWithIndex< TImage >A base class for multi-dimensional iterators templated over image type that are designed to efficiently keep track of the iterator position
itk::ImageContainerInterface< TElementIdentifier, TElement >
itk::ImageDuplicator< TInputImage >This helper class create an image which is perfect copy of the input image
itk::ImageFileReader< TOutputImage, ConvertPixelTraits >Data source that reads image data from a single file
itk::ImageFileReaderExceptionBase exception class for IO conflicts
itk::ImageFileWriter< TInputImage >Writes image data to a single file
itk::ImageFileWriterExceptionBase exception class for IO problems during writing
itk::ImageFunction< TInputImage, TOutput, TCoordRep >Evaluates a function of an image at specified position
itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >Base class for ImageGaussianModelEstimator object
itk::ImageHelper< NImageDimension, NLoop >Fast Index/Offset computation
itk::ImageIOBaseAbstract superclass defines image IO interface
itk::ImageIOFactoryCreate instances of ImageIO objects using an object factory
itk::ImageIORegionAn ImageIORegion represents a structured region of data
itk::ImageIORegionAdaptor< VDimension >Helper class for converting ImageRegions into ImageIORegions and back
itk::ImageIterator< TImage >A multi-dimensional iterator templated over image type
itk::ImageIteratorWithIndex< TImage >A base class for multi-dimensional iterators templated over image type that are designed to efficiently keep track of the iterator position
itk::Statistics::ImageJointDomainTraits< TImage >This class provides the type defintion for the measurement vector in the joint domain (range domain -- pixel values + spatial domain -- pixel's physical coordinates)
itk::ImageKernelOperator< TPixel, VDimension, TAllocator >A NeighborhoodOperator whose coefficients are from an image
itk::ImageKmeansModelEstimator< TInputImage, TMembershipFunction >Base class for ImageKmeansModelEstimator object
itk::ImageLinearConstIteratorWithIndex< TImage >A multi-dimensional image iterator that visits image pixels within a region in a "scan-line" order
itk::ImageLinearIteratorWithIndex< TImage >A multi-dimensional image iterator that visits image pixels within a region in a "scan-line" order
itk::ImageMaskSpatialObject< TDimension >Implementation of an image mask as spatial object
itk::fem::ImageMetricLoad< TMoving, TFixed >General image pair load that uses the itkImageToImageMetrics
itk::fem::ImageMetricLoadImplementation< TLoadClass >
itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >Base class for model estimation from images used for classification
itk::ImageMomentsCalculator< TImage >Compute moments of an n-dimensional image
itk::ImagePCADecompositionCalculator< TInputImage, TBasisImage >Decomposes an image into directions along basis components
itk::ImagePCAShapeModelEstimator< TInputImage, TOutputImage >Base class for ImagePCAShapeModelEstimator object
itk::ImageRandomConstIteratorWithIndex< TImage >A multi-dimensional image iterator that visits a random set of pixels within an image region
itk::ImageRandomIteratorWithIndex< TImage >A multi-dimensional image iterator that visits a random set of pixels within an image region
itk::ImageRandomNonRepeatingConstIteratorWithIndex< TImage >A multi-dimensional image iterator that visits a random set of pixels within an image region. All pixels in the image will be visited before any are repeated. A priority image may be passed to the interator which will cause it to select certain sets of pixels (those with lower priority values) before others
itk::ImageRandomNonRepeatingIteratorWithIndex< TImage >A multi-dimensional image iterator that visits image pixels within a region in a random order, without repeating
itk::ImageRegion< VImageDimension >An image region represents a structured region of data
itk::ImageRegionConstIterator< TImage >A multi-dimensional iterator templated over image type that walks a region of pixels
itk::ImageRegionConstIteratorWithIndex< TImage >A multi-dimensional iterator templated over image type that walks an image region and is specialized to keep track of its index location
itk::ImageToImageFilterDetail::ImageRegionCopier< D1, D2 >Function object used to dispatching to a routine to copy a region (start index and size)
itk::ImageRegionExclusionConstIteratorWithIndex< TImage >Multi-dimensional image iterator that walks an image region, excluding a second region contained within the first
itk::ImageRegionExclusionIteratorWithIndex< TImage >Multi-dimensional image iterator that walks an image region, excluding a second region contained within the first
itk::ImageRegionIterator< TImage >A multi-dimensional iterator templated over image type that walks a region of pixels
itk::ImageRegionIteratorWithIndex< TImage >A multi-dimensional iterator templated over image type that walks pixels within a region and is specialized to keep track of its image index location
itk::ImageRegionMultidimensionalSplitter< VImageDimension >Divide a region into several pieces
itk::ImageRegionReverseConstIterator< TImage >A multi-dimensional image iterator designed to walk a specified image region in reverse
itk::ImageRegionReverseIterator< TImage >Multi-dimensional image iterator which only walks a region
itk::ImageRegionSplitter< VImageDimension >Divide a region into several pieces
itk::ImageRegistrationMethod< TFixedImage, TMovingImage >Base class for Image Registration Methods
itk::ImageReverseConstIterator< TImage >Multi-dimensional image iterator
itk::ImageReverseIterator< TImage >A multi-dimensional image iterator designed to walk a specified region in reverse
itk::ImageSeriesReader< TOutputImage >Data source that reads image data from a series of disk files
itk::ImageSeriesWriter< TInputImage, TOutputImage >Writes image data to a series of data files
itk::ImageSeriesWriterExceptionBase exception class for IO problems during writing
itk::ImageShapeModelEstimatorBase< TInputImage, TOutputImage >Base class for statistical shape model estimation
itk::ImageSliceConstIteratorWithIndex< TImage >Multi-dimensional image iterator which only walks a region
itk::ImageSliceIteratorWithIndex< TImage >A multi-dimensional image iterator that extends the ImageLinearIteratorWithIndex from iteration along lines in an image to iteration along both lines and planes (slices) within an image. A slice is defined as a 2D plane spanned by two vectors pointing along orthogonal coordinate axes
itk::ImageSource< TOutputImage >Base class for all process objects that output image data
itk::ImageSpatialObject< TDimension, TPixelType >Implementation of an image as spatial object
itk::Statistics::ImageToCooccurrenceListAdaptor< TImage >Converts pixel data into a list of pairs in order to compute a cooccurrence Histogram
itk::Statistics::ImageToHistogramFilter< TImageType >This class generates an histogram from an image
itk::Statistics::ImageToHistogramGenerator< TImageType >This class generates an histogram from an image
itk::ImageToImageFilter< TInputImage, TOutputImage >Base class for filters that take an image as input and produce an image as output
itk::ImageToImageMetric< TFixedImage, TMovingImage >Computes similarity between regions of two images
itk::Statistics::ImageToListAdaptor< TImage, TMeasurementVector >This class provides ListSampleBase interfaces to ITK Image
itk::Statistics::ImageToListGenerator< TImage, TMaskImage >The class takes an image as input and generates a list sample as output
itk::Statistics::ImageToListSampleAdaptor< TImage >This class provides ListSample interface to ITK Image
itk::Statistics::ImageToListSampleFilter< TImage, TMaskImage >The class takes an image as input and generates a list sample as output
itk::ImageToMeshFilter< TInputImage, TOutputMesh >ImageToMeshFilter is the base class for all process objects that output Mesh data and require image data as input. Specifically, this class defines the SetInput() method for defining the input to a filter
itk::ImageToParametricSpaceFilter< TInputImage, TOutputMesh >Generate a mesh of parametric space from input images
itk::ImageToPathFilter< TInputImage, TOutputPath >Base class for filters that take an image as input and produce an path as output
itk::ImageToSpatialObjectMetric< TFixedImage, TMovingSpatialObject >Computes similarity between a moving spatial obejct and an Image to be registered
itk::ImageToSpatialObjectRegistrationMethod< TFixedImage, TMovingSpatialObject >Base class for Image Registration Methods
itk::ImageToVectorImageFilter< TInputImage >This class takes as input 'n' itk::Image's and composes them into a single itk::VectorImage
itk::ImageTransformHelper< NImageDimension, R, C >Fast index/physical index computation
itk::ImageVoxel
itk::ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >This class implements the filter for computing the normal vectors from a scalar implicit function (i.e. a levelset image) and processing them
itk::ImportImageContainer< TElementIdentifier, TElement >
itk::ImportImageFilter< TPixel, VImageDimension >Import data from a standard C array into an itk::Image
itk::Concept::IncrementDecrementOperators< T >
itk::IndentControl indentation during Print() invocation
itk::Index< VIndexDimension >Represent a n-dimensional index in a n-dimensional image
itk::IndexedContainerInterface< TElementIdentifier, TElement >
itk::Functor::IndexLexicographicCompare< VIndexDimension >Order Index instances lexicographically
itk::fem::INITClassClass that is used in FEM_CLASS_INIT macro
itk::InitializeEvent
itk::InOrderTreeIterator< TTreeType >
itk::InPlaceImageFilter< TInputImage, TOutputImage >Base class for filters that take an image as input and overwrite that image as the output
itk::InPlaceLabelMapFilter< TInputImage >Base class for filters that takes an image as input and overwrites that image as the output
itk::Statistics::InputFunctionBase< TMeasurementVector, TTargetVector >
itk::ImageToImageFilterDetail::IntDispatch< int >Templated class to produce a unique type for each integer
itk::Functor::IntensityLinearTransform< TInput, TOutput >
itk::IntensityWindowingImageFilter< TInputImage, TOutputImage >Applies a linear transformation to the intensity levels of the input Image that are inside a user-defined interval. Values below this interval are mapped to a constant. Values over the interval are mapped to another constant
itk::Functor::IntensityWindowingTransform< TInput, TOutput >
InterfaceWrapper for FFTW API
itk::InteriorExteriorMeshFilter< TInputMesh, TOutputMesh, TSpatialFunction >InteriorExteriorMeshFilter takes an itk::Mesh and extracts from it a Sub-Mesh such that all its points Evaluate > 0 in an itk::SpatialFunction provided by the user
itk::InteriorExteriorSpatialFunction< VDimension, TInput >Returns whether or not a location is "inside" or "outside" a function
itk::InterpolateImageFilter< TInputImage, TOutputImage >Interpolate an image from two N-D images
itk::InterpolateImageFunction< TInputImage, TCoordRep >Base class for all image interpolaters
itk::InterpolateImagePointsFilter< TInputImage, TOutputImage, TCoordType, InterpolatorType >Resamples an image at the coordinates specified by the user
itk::IntrinsicMatrixCoefficients< TInputMesh >Compute a mtrix filled by intrinsic Coefficients of the edge, wherever two vertices are connected by an edge
itk::InvalidRequestedRegionError
InvalidRequestRegionError
itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >Computes the inverse of a deformation field
itk::InverseEuclideanDistanceMatrixCoefficients< TInputMesh >Compute a matrix filed with the inverse of the euclidian distance wherever two vertices are connected by an edge
itk::Functor::InvertIntensityFunctor< InputPixelType >
itk::InvertIntensityImageFilter< TInputImage, TOutputImage >Invert intensity of an image
itk::Functor::InvertIntensityTransform< TInput, TOutput >
itk::IOCommonCentralized funtionality for IO classes
itk::IPLCommonImageIOClass that defines how to read GE4 file format
itk::IPLFileNameList-- stores filename+info to be enumerated for IPLCommonImageIO
itk::IPLFileSortInfo
IPLSortInfo-- holds info on one file for IPLCommonImageIO
itk::Concept::IsFixedPoint< T >
itk::Concept::IsFloatingPoint< T >
itk::Concept::IsInteger< T >
itk::Concept::IsNonInteger< T >
itk::IsoContourDistanceImageFilter< TInputImage, TOutputImage >Compute an approximate distance from an interpolated isocontour to the close grid points
itk::IsolatedConnectedImageFilter< TInputImage, TOutputImage >Label pixels that are connected to one set of seeds but not another
itk::IsolatedWatershedImageFilter< TInputImage, TOutputImage >Isolate watershed basins using two seeds
itk::IsotropicFourthOrderLevelSetImageFilter< TInputImage, TOutputImage >This class implements the 4th-order level set isotropic diffusion (smoothing) PDE
itk::IterationEvent
itk::IterationReporterImplements iterations tracking for a filter
itk::IterativeInverseDeformationFieldImageFilter< TInputImage, TOutputImage >Computes the inverse of a deformation field
itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType >
itk::ShapedNeighborhoodIterator< TImage, TBoundaryCondition >::Iterator
itk::VectorContainer< TElementIdentifier, TElement >::Iterator
itk::Statistics::Histogram< TMeasurement, VMeasurementVectorSize, TFrequencyContainer >::Iterator
itk::Statistics::ImageToListAdaptor< TImage, TMeasurementVector >::Iterator
itk::Statistics::ListSample< TMeasurementVector >::Iterator
itk::Statistics::PointSetToListAdaptor< TPointSet >::Iterator
itk::Statistics::Subsample< TSample >::Iterator
itk::Statistics::VariableDimensionHistogram< TMeasurement, TFrequencyContainer >::Iterator
itk::IndexedContainerInterface< TElementIdentifier, TElement >::IteratorSupport iteration operations through a container. Dereferencing the iterator must provide an object with the following methods: ElementIdentifier Index(void) const; Element& Value(void);
itk::Statistics::ImageToListSampleAdaptor< TImage >::Iterator
itk::Statistics::JointDomainImageToListSampleAdaptor< TImage >::Iterator
itk::MapContainer< TElementIdentifier, TElement >::IteratorThe non-const iterator type for the map
itk::Statistics::MembershipSample< TSample >::Iterator
itk::Statistics::PointSetToListSampleAdaptor< TPointSet >::Iterator
Histogram::Iterator
ImageToListSampleAdaptor::Iterator
ListSample::Iterator
PointSetToListSampleAdaptor::Iterator
itk_simple_alloc< T, Alloc >
itkBSplineCenteredL2ResampleImageFilterBaseUses the "Centered L2" B-Spline pyramid implementation of B-Spline Filters to up/down sample an image by a factor of 2
itk::fem::ItpackSparseMatrixCompressed row sparse matrix representation that makes use of itpack to dynamically assemble the matrix
itk::Functor::JetColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::Functor::JoinFunctor< TPixel1, TPixel2 >Join the components of two pixel types into a single pixel type
itk::JoinImageFilter< TInputImage1, TInputImage2 >Join two images, resulting in an image where each pixel has the components of the first image followed by the components of the second image
itk::JoinSeriesImageFilter< TInputImage, TOutputImage >Join N-D images into an (N+1)-D image
itk::Statistics::JointDomainImageToListAdaptor< TImage >This adaptor returns measurement vectors composed of an image pixel's range domain value (pixel value) and spatial domain value (pixel's physical coordiantes)
itk::Statistics::JointDomainImageToListSampleAdaptor< TImage >This adaptor returns measurement vectors composed of an image pixel's range domain value (pixel value) and spatial domain value (pixel's physical coordiantes)
itk::JPEGImageIOImageIO object for reading and writing JPEG images
itk::JPEGImageIOFactoryCreate instances of JPEGImageIO objects using an object factory
itk::KalmanLinearEstimator< T, VEstimatorDimension >Implement a linear recursive estimator
itk::KappaSigmaThresholdImageCalculator< TInputImage, TMaskImage >Compute moments of an n-dimensional image
itk::KappaSigmaThresholdImageFilter< TInputImage, TMaskImage, TOutputImage >Threshold an image using multiple Otsu Thresholds
itk::KappaStatisticImageToImageMetric< TFixedImage, TMovingImage >Computes similarity between two binary objects to be registered
itk::Statistics::KdTree< TSample >This class provides methods for k-nearest neighbor search and related data structures for a k-d tree
itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >Fast k-means algorithm implementation using k-d tree structure
itk::Statistics::KdTreeGenerator< TSample >This class generates a KdTree object without centroid information
itk::Statistics::KdTreeNode< TSample >This class defines the interface of its derived classes
itk::Statistics::KdTreeNonterminalNode< TSample >This is a subclass of the KdTreeNode
itk::Statistics::KdTreeTerminalNode< TSample >This class is the node that doesn't have any child node. The IsTerminal method returns true for this class. This class stores the instance identifiers belonging to this node, while the nonterminal nodes do not store them. The AddInstanceIdentifier and GetInstanceIdentifier are storing and retrieving the instance identifiers belonging to this node
itk::Statistics::KdTreeWeightedCentroidNonterminalNode< TSample >This is a subclass of the KdTreeNode
itk::KernelFunctionKernel used for density estimation and nonparameteric regression
itk::KernelImageFilter< TInputImage, TOutputImage, TKernel >A base class for all the filters working on an arbitrary shaped neighborhood
itk::KernelTransform< TScalarType, NDimensions >
itk::KLMDynamicBorderArray< TBorder >Object maintaining a reference to a list of borders associated with a region
itk::KLMRegionGrowImageFilter< TInputImage, TOutputImage >Base class for a region growing object that performs energy-based region growing for multiband images
itk::KLMSegmentationBorderBase class for KLMSegmentationBorder object
itk::KLMSegmentationRegionBase class for KLMSegmentationRegion object
itk::KullbackLeiblerCompareHistogramImageToImageMetric< TFixedImage, TMovingImage >Computes the Kubler Lieblach(KL) metric between the histogram of the two images to be registered and a training histogram
itk::Functor::KurtosisLabelObjectAccessor< TLabelObject >
itk::LabelContourImageFilter< TInputImage, TOutputImage >Labels the pixels on the border of the objects in a labeled image
itk::LabelGeometryImageFilter< TLabelImage, TIntensityImage >::LabelGeometryGeometry stored per label
itk::LabelGeometryImageFilter< TLabelImage, TIntensityImage >Given a label map and an optional intensity image, compute geometric features
itk::LabelImageToLabelMapFilter< TInputImage, TOutputImage >Convert a labeled image to a label collection image
itk::LabelImageToShapeLabelMapFilter< TInputImage, TOutputImage >Converts a label image to a label map and valuates the shape attributes
itk::LabelImageToStatisticsLabelMapFilter< TInputImage, TFeatureImage, TOutputImage >Convenient class to convert a label image to a label map and valuate the statistics attributes at once
itk::Functor::LabelLabelObjectAccessor< TLabelObject >
itk::LabelMap< TLabelObject >Templated n-dimensional image to store labeled objects
itk::LabelMapFilter< TInputImage, TOutputImage >Base class for filters that take an image as input and overwrite that image as the output
itk::LabelMapToBinaryImageFilter< TInputImage, TOutputImage >Convert a LabelMap to a binary image
itk::LabelMapToLabelImageFilter< TInputImage, TOutputImage >Converts a LabelMap to a labeled image
itk::LabelObject< TLabel, VImageDimension >The base class for the representation of an labeled binary object in an image
itk::Functor::LabelObjectComparator< TLabelObject, TAttributeAccessor >
itk::LabelObjectLine< VImageDimension >
itk::Functor::LabelObjectLineComparator< TLabelObjectLine >
LabelObjectLineComparatorPerforms a comparison of l1 < l2. Returns true if l1 is strictly less than l2
itk::Functor::LabelObjectReverseComparator< TLabelObject, TAttributeAccessor >
itk::Functor::LabelOverlayFunctor< TInputPixel, TLabel, TRGBPixel >Functor for applying a colormap to a label image and combine it with a grayscale image
itk::LabelOverlayImageFilter< TInputImage, TLabelImage, TOutputImage >Apply a colormap to a label image and put it on top of the input image
itk::LabelPerimeterEstimationCalculator< TInputImage >Estimates the perimeter of a label object
itk::LabelShapeKeepNObjectsImageFilter< TInputImage >Keep N objects according to their shape attributes
itk::LabelShapeOpeningImageFilter< TInputImage >Remove the objects according to the value of their shape attribute
itk::LabelStatisticsImageFilter< TInputImage, TLabelImage >::LabelStatisticsStatistics stored per label
itk::LabelStatisticsImageFilter< TInputImage, TLabelImage >Given an intensity image and a label map, compute min, max, variance and mean of the pixels associated with each label or segment
itk::LabelStatisticsKeepNObjectsImageFilter< TInputImage, TFeatureImage >Keep N objects according to their statistics attributes
itk::LabelStatisticsOpeningImageFilter< TInputImage, TFeatureImage >Remove the objects according to the value of their statistics attribute
itk::Functor::LabelToRGBFunctor< TLabel, TRGBPixel >Functor for converting labels into RGB triplets
itk::LabelToRGBImageFilter< TLabelImage, TOutputImage >Apply a colormap to a label image
itk::LabelVotingImageFilter< TInputImage, TOutputImage >This filter performs pixelwise voting among an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image)
itk::Function::LanczosWindowFunction< VRadius, TInput, TOutput >Window function for sinc interpolation.

\[ w(x) = \textrm{sinc} ( \frac{x}{m} ) \]

Note: Paper referenced in WindowedSincInterpolateImageFunction gives an incorrect definition of this window function

itk::LandmarkBasedTransformInitializer< TTransform, TFixedImage, TMovingImage >LandmarkBasedTransformInitializer is a helper class intended to The class computes the transform that aligns the fixed and moving images given a set of landmarks. The class is templated over the Transform type. The transform computed gives the best fit transform that maps the fixed and moving images in a least squares sense. The indices are taken to correspond, so point 1 in the first set will get mapped close to point 1 in the second set, etc. An equal number of fixed and moving landmarks need to be specified using SetFixedLandmarks() SetMovingLandmarks(). Any number of landmarks may be specified. Call InitializeTransform() to initialize the transform
itk::LandmarkSpatialObject< TDimension >Representation of a Landmark based on the spatial object classes
itk::LaplacianImageFilter< TInputImage, TOutputImage >
itk::LaplacianOperator< TPixel, VDimension, TAllocator >
itk::LaplacianRecursiveGaussianImageFilter< TInputImage, TOutputImage >Computes the Laplacian of an image by convolution with the second derivative of a Gaussian
itk::LaplacianSegmentationLevelSetFunction< TImageType, TFeatureImageType >This function is used in LaplacianSegmentationImageFilter to segment structures in an image based Laplacian edges
itk::LaplacianSegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in images based on a second derivative image features
itk::LaplacianSharpeningImageFilter< TInputImage, TOutputImage >
itk::Statistics::LayerBase< TMeasurementVector, TTargetVector >
itk::LBFGSBOptimizerLimited memory Broyden Fletcher Goldfarb Shannon minimization with simple bounds
LBFGSBOptimizerHelperWrapper helper around vnl_lbfgsb
itk::LBFGSOptimizerWrap of the vnl_lbfgs algorithm
itk::LeafTreeIterator< TTreeType >
itk::Statistics::LearningFunctionBase< LayerType, TTargetVector >
LearningFunctionBaseThe LearningFunctionBase is the base class for all the learning strategies. These include error back propagation, bp+momentum, conjugte gradient descent, quick prop. This class specifies how the errors are backpropagated for a layer. They take a LayerBase object as input and compute the input for the layers input weightset
itk::Statistics::MeanShiftModeCacheMethod< TMeasurementVector >::LessMeasurementVector
itk::Concept::LessThanComparable< T1, T2 >
itk::LevelOrderTreeIterator< TTreeType >
itk::LevelSetFunction< TImageType >The LevelSetFunction class is a generic function object which can be used to create a level set method filter when combined with an appropriate finite difference image filter. (See FiniteDifferenceImageFilter.)
itk::LevelSetFunctionWithRefitTerm< TImageType, TSparseImageType >This class extends the LevelSetFunction class by adding a grow term based on a target curvature stored in a sparse image
itk::LevelSetMotionRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >Deformably register two images using level set motion
itk::LevelSetMotionRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >
itk::LevelSetNeighborhoodExtractor< TLevelSet >Locate pixels of a particular level set
itk::LevelSetNode< TPixel, VSetDimension >Represent a node in a level set
itk::LevelSetTypeDefault< TLevelSet >Level set type information
itk::LevelSetVelocityNeighborhoodExtractor< TLevelSet, TAuxValue, VAuxDimension >Locate pixels of a particular level set
itk::LevenbergMarquardtOptimizerWrap of the vnl_levenberg_marquardt algorithm
itk::LightObjectLight weight base class for most itk classes
itk::LightProcessObjectLightProcessObject is the base class for all process objects (source, filters, mappers) in the Insight data processing pipeline
itk::LinearInterpolateImageFunction< TInputImage, TCoordRep >Linearly interpolate an image at specified positions
itk::fem::LinearSystemWrapperDefines all functions required by Solver class to allocate, assemble and solve a linear system of equation
itk::fem::LinearSystemWrapperDenseVNLLinearSystemWrapper class that uses VNL numeric library functions to define a sparse linear system of equations
itk::fem::LinearSystemWrapperItpackLinearSystemWrapper class that uses Itpack numeric library functions to define and solve a sparse linear system of equations
itk::fem::LinearSystemWrapperVNLLinearSystemWrapper class that uses VNL numeric library functions to define a sparse linear system of equations
itk::LineCell< TCellInterface >
itk::LineConstIterator< TImage >Iterator that walks a Bresenham line through an ND image
itk::LineIterator< TImage >Iterator that walks a Bresenham line through an ND image
itk::LineSpatialObject< TDimension >Representation of a Line based on the spatial object classes
itk::LineSpatialObjectPoint< TPointDimension >Point used for a line definition
list
itk::ListNode< TValueType >
itk::Statistics::ListSample< TMeasurementVector >This class is the native implementation of the ListSampleBase
itk::Statistics::ListSampleBase< TMeasurementVector >This class is the base class for Samples that store measurements in a list
itk::Statistics::ListSampleToHistogramFilter< TListSample, THistogram >Imports data from ListSample object to Histogram object
itk::Statistics::ListSampleToHistogramGenerator< TListSample, THistogramMeasurement, TFrequencyContainer, TMeasurementVectorLength >Generates a Histogram using the data from the ListSample object
itk::fem::LoadGeneral abstract load base class
itk::fem::LoadBCGeneric essential (Dirichlet) boundary conditions
itk::fem::LoadBCMFCGeneric linear multi freedom displacement constraint in global coordinate system
itk::fem::LoadEdgeA generic load that can be applied to an edge of the element
itk::fem::LoadElementVirtual element load base class
itk::fem::LoadGravAbstract gravity load class
itk::fem::LoadGravConstConstant gravity load class
itk::fem::LoadImplementationGenericBodyLoadClass that holds a templated generic body load implementation
itk::fem::LoadImplementationGenericLandmarkLoadClass that holds a templated generic landmark load implementation
itk::fem::LoadImplementationTest< TLoadClass >Example implementation of templated LoadTest class
itk::fem::LoadLandmarkThis load is derived from the motion of a specific landmark
itk::fem::LoadNodeThis load is applied on a specific point within the system
itk::fem::LoadPointThis load is applied on a point in an element
itk::fem::LoadTest< TClass >Example to show how to define templated load classes
itk::Function::Log< TInput, TOutput >
itk::Function::Log10< TInput, TOutput >
itk::Log10ImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_log10() of its pixels
itk::Log10ImageFilter< TInputImage, TOutputImage >Computes the vcl_log10(x) pixel-wise
itk::Accessor::Log10PixelAccessor< TInternalType, TExternalType >Give access to the vcl_log10() function of a value
itk::LoggerClass Logger is meant for logging information during a run
itk::LoggerBaseClass LoggerBase is meant for logging information during a run
itk::LoggerManagerClass LoggerManager is meant for centrally managing loggers
itk::LoggerOutputThis class is meant for overriding itk::OutputWindow to redirect messages to itk::Logger
itk::LoggerThreadWrapper< SimpleLoggerType >Class LoggerThreadWrapper is meant for providing logging service as a separate thread
itk::Concept::LogicalOperators< T1, T2, T3 >
itk::LogImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_log() of its pixels
itk::LogImageFilter< TInputImage, TOutputImage >Computes the vcl_log(x) pixel-wise
itk::Statistics::LogLikelihoodGoodnessOfFitFunction< TInputHistogram >Calculates loglikelihood ratio statistics
itk::LogOutputClass LogOutput represents an output stream
itk::Accessor::LogPixelAccessor< TInternalType, TExternalType >Give access to the vcl_log() function of a value
itk::Statistics::LogSigmoidTransferFunction< ScalarType >
itk::LSMImageIOImageIO class for reading LSM (Zeiss) images LSM is a line of confocal laser scanning microscopes produced by the Zeiss company LSM files are essentially extensions of the TIFF multiple image stack file format
itk::LSMImageIOFactoryCreate instances of LSMImageIO objects using an object factory
itk::Functor::MagnitudeAndPhaseToComplex< TInput1, TInput2, TOutput >
itk::MagnitudeAndPhaseToComplexImageFilter< TInputPixel1, TInputPixel2, TOutputPixel, NDimension >Implements pixel-wise conversion of magnitude and phase data into complex voxels
itk::Statistics::MahalanobisDistanceMembershipFunction< TVector >MahalanobisDistanceMembershipFunction class represents MahalanobisDistance Density Function
itk::Statistics::MahalanobisDistanceMetric< TVector >MahalanobisDistanceMetric class computes a Mahalanobis distance given a mean and covariance
itk::MahalanobisDistanceThresholdImageFunction< TInputImage, TCoordRep >Returns true if the pixel value of a vector image has a Mahalanobis distance below the value specified by the threshold
itk::Functor::MakeJoin< TImage1, TImage2 >
MallinfoMemoryUsageObserver
MallinfoMemoryUsageObserver
itk::Statistics::ManhattanDistanceMetric< TVector >Euclidean distance function
itk::MapContainer< TElementIdentifier, TElement >
itk::MapData
itk::MapFileParser< TMapData >
itk::MapRecordMapRecord class
itk::MaskedMovingHistogramImageFilter< TInputImage, TMaskImage, TOutputImage, TKernel, THistogram >
itk::MaskedRankHistogram< TInputPixel >
itk::MaskedRankHistogramMap< TInputPixel, TCompare >
itk::MaskedRankHistogramVec< TInputPixel, TCompare >
itk::MaskedRankImageFilter< TInputImage, TMaskImage, TOutputImage, TKernel >Rank filter of a greyscale image
itk::Statistics::MaskedScalarImageToGreyLevelCooccurrenceMatrixGenerator< TImageType, THistogramFrequencyContainer >This class computes a grey-level co-occurence matrix (histogram) from a given image and mask. GLCM's are used for image texture description
itk::MaskImageFilter< TInputImage, TMaskImage, TOutputImage >Implements an operator for pixel-wise masking of the input image with the mask
itk::Functor::MaskInput< TInput, TMask, TOutput >
itk::MaskNegatedImageFilter< TInputImage, TMaskImage, TOutputImage >Implements an operator for pixel-wise masking of the input image with the negative of a mask
itk::Functor::MaskNegatedInput< TInput, TMask, TOutput >
itk::MaskNeighborhoodOperatorImageFilter< TInputImage, TMaskImage, TOutputImage, TOperatorValueType >Applies a single NeighborhoodOperator to an image, processing only those pixels that are under a mask
itk::MatchCardinalityImageToImageMetric< TFixedImage, TMovingImage >Computes similarity between two objects to be registered
itk::fem::MaterialBase class for storing all the implicit material and other properties required to fully define the element class
itk::fem::MaterialLinearElasticityLinear elasticity material class
itk::MatlabTransformIO
itk::MatlabTransformIOFactoryCreate instances of MatlabTransformIO objects using an object factory
itk::Matrix< T, NRows, NColumns >A templated class holding a M x N size Matrix This class contains a vnl_matrix_fixed in order to make all the vnl mathematical methods available
itk::MatrixCoefficients< TInputMesh >Superclass for all the matrix coefficients computation classes
itk::Functor::MatrixIndexSelection< TInput, TOutput >
itk::MatrixIndexSelectionImageFilter< TInputImage, TOutputImage >Extracts the selected indices of a matrix image that is the input pixel type
itk::MatrixOffsetTransformBase< TScalarType, NInputDimensions, NOutputDimensions >
itk::MatrixResizeableDataObject< TItemType >Allows for a vnl matrix to be a data object with the flexibility of being resizable
itk::MattesMutualInformationImageToImageMetric< TFixedImage, TMovingImage >Computes the mutual information between two images to be registered using the method of Mattes et al
itk::MaxFunctor< TPixel >
itk::Function::Maximum< TInput1, TInput2, TOutput >
itk::Functor::Maximum1< TInput, TOutput >
itk::Function::MaximumAccumulator< TInputPixel >
itk::MaximumDecisionRuleA Decision rule that choose the class of which discriminant score is the largest
itk::Statistics::MaximumDecisionRule2A Decision rule that choose the class of which discriminant score is the largest. This class will replace the MaximumDecisionRule in Code/Common
itk::MaximumImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements a pixel-wise operator Max(a,b) between two images
itk::Functor::MaximumIndexLabelObjectAccessor< TLabelObject >
itk::Functor::MaximumLabelObjectAccessor< TLabelObject >
itk::MaximumProjectionImageFilter< TInputImage, TOutputImage >Maximum projection
itk::MaximumRatioDecisionRuleThis rule returns $i$ if $\frac{f_{i}(\overrightarrow{x})}{f_{j}(\overrightarrow{x})} > \frac{K_{j}}{K_{i}}$ for all $j \not= i$, where the $i$ is the index of a class which has membership function $f_{i}$ and its prior value (usually, the a priori probability or the size of a class) is $K_{i}$
itk::Statistics::MaximumRatioDecisionRule2This rule returns $i$ if $\frac{f_{i}(\overrightarrow{x})}{f_{j}(\overrightarrow{x})} > \frac{K_{j}}{K_{i}}$ for all $j \not= i$, where the $i$ is the index of a class which has membership function $f_{i}$ and its prior value (usually, the a priori probability or the size of a class) is $K_{i}$
itk::MaxMeasureBoundCriterion< TMesh, TElement, TMeasure, TPriorityQueueWrapper >
itk::MaxPriorityQueueElementWrapper< TElement, TElementPriority, TElementIdentifier >
itk::Function::MeanAccumulator< TInputPixel, TAccumulate >
itk::Statistics::MeanCalculator< TSample >Calculates sample mean
itk::MeanImageFilter< TInputImage, TOutputImage >Applies an averaging filter to an image
itk::MeanImageFunction< TInputImage, TCoordRep >Calculate the mean value in the neighborhood of a pixel
itk::Functor::MeanLabelObjectAccessor< TLabelObject >
itk::MeanProjectionImageFilter< TInputImage, TOutputImage, TAccumulate >Mean projection
itk::MeanReciprocalSquareDifferenceImageToImageMetric< TFixedImage, TMovingImage >Computes similarity between two objects to be registered
itk::MeanReciprocalSquareDifferencePointSetToImageMetric< TFixedPointSet, TMovingImage >Computes similarity between pixel values of a point set and intensity values in an image
itk::Statistics::MeanSampleFilter< TSample >Given a sample, this filter computes the sample mean
itk::Statistics::MeanShiftModeCacheMethod< TMeasurementVector >This class stores mappings between a query point and its resulting mode point
itk::Statistics::MeanShiftModeSeekerBase< TSample >Evolves the mode. This is the base class for any mean shift mode seeking algorithm classes
itk::Statistics::MeanSquaredErrorFunction< TMeasurementVector, ScalarType >
itk::MeanSquareRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >
itk::MeanSquaresHistogramImageToImageMetric< TFixedImage, TMovingImage >Computes mean squared difference similarity measure between two images to be registered
itk::MeanSquaresImageToImageMetric< TFixedImage, TMovingImage >Computes similarity between two objects to be registered
itk::MeanSquaresPointSetToImageMetric< TFixedPointSet, TMovingImage >Computes similarity between pixel values of a point set and intensity values of an image
itk::Statistics::MeasurementVectorPixelTraits< TPixelType >
itk::Statistics::MeasurementVectorPixelTraits< char >
itk::Statistics::MeasurementVectorPixelTraits< double >
itk::Statistics::MeasurementVectorPixelTraits< float >
itk::Statistics::MeasurementVectorPixelTraits< signed char >
itk::Statistics::MeasurementVectorPixelTraits< signed int >
itk::Statistics::MeasurementVectorPixelTraits< signed long >
itk::Statistics::MeasurementVectorPixelTraits< signed short >
itk::Statistics::MeasurementVectorPixelTraits< unsigned char >
itk::Statistics::MeasurementVectorPixelTraits< unsigned int >
itk::Statistics::MeasurementVectorPixelTraits< unsigned long >
itk::Statistics::MeasurementVectorPixelTraits< unsigned short >
itk::MeasurementVectorTraits
itk::Statistics::MeasurementVectorTraits
itk::Statistics::MeasurementVectorTraitsTypes< TMeasurementVector >
itk::Statistics::MeasurementVectorTraitsTypes< std::vector< T > >
itk::MedialNodePairCorrespondenceProcess< TSourceImage >This process takes as inputs two core atom images, the distance matrices of the two images, and the unary correspondence matrix between the two images in order to produce an itkCorrespondenceDataStructure containing correspondences between pairs (node cliques of size 2) in the images
itk::MedialNodeTripletCorrespondenceProcess< TSourceImage >This process takes as inputs two core atom images, a pair correspondence data structure for the two images, and the distance matrices of the two images in order to produce an itkCorrespondenceDataStructure containing correspondences between triplets (node cliques of size 3) in the images
itk::Function::MedianAccumulator< TInputPixel >
itk::MedianImageFilter< TInputImage, TOutputImage >Applies a median filter to an image
itk::MedianImageFunction< TInputImage, TCoordRep >Calculate the median value in the neighborhood of a pixel
itk::Functor::MedianLabelObjectAccessor< TLabelObject >
itk::MedianProjectionImageFilter< TInputImage, TOutputImage >Median projection
itk::MemberCommand< T >Command subclass that calls a pointer to a member function
itk::Statistics::MembershipFunctionBase< TVector >MembershipFunctionBase class declares common interfaces for membership functions
itk::Statistics::MembershipSample< TSample >Container for storing the instance-identifiers of other sample with their associated class labels
itk::Statistics::MembershipSampleGenerator< TInputSample, TClassMaskSample >MembershipSampleGenerator generates a MembershipSample object using a class mask sample
itk::ObjectStore< TObjectType >::MemoryBlock
itk::MemoryProbeClass for computing the memory allocated between two points in the code
itk::MemoryProbesCollectorBaseClass for aggregating a set of memory probes
MemoryUsageObserver
MemoryUsageObserverThe MemoryUsageObserver provides the memory usage of the process
itk::MemoryUsageObserverBase
itk::watershed::SegmentTree< TScalarType >::merge_comp
itk::watershed::SegmentTree< TScalarType >::merge_t
itk::MergeLabelMapFilter< TImage >Merges two Label Maps using different methods to create the product
itk::Statistics::MersenneTwisterRandomVariateGeneratorMersenneTwisterRandom random variate generator
itk::Mesh< TPixelType, VDimension, TMeshTraits >Implements the N-dimensional mesh structure
MeshFunctionBaseBase class for mesh function object modifiers
MeshFunctionBaseFuse the incoming edge and it's Onext() follower (like a zipper does)
itk::MeshRegionA mesh region represents an unstructured region of data
itk::MeshSource< TOutputMesh >Base class for all process objects that output mesh data
itk::MeshSpatialObject< TMesh >Implementation of an Mesh as spatial object
itk::MeshToMeshFilter< TInputMesh, TOutputMesh >MeshToMeshFilter is the base class for all process objects that output mesh data, and require mesh data as input. Specifically, this class defines the SetInput() method for defining the input to a filter
itk::MetaArrayReader
itk::MetaArrayWriter
itk::MetaArrowConverter< NDimensions >
itk::MetaBlobConverter< NDimensions >
itk::MetaContourConverter< NDimensions >
itk::MetaDataDictionary
itk::MetaDataDictionary::MetaDataDictionaryMapType
itk::MetaDataObject< MetaDataObjectType >
itk::MetaDataObjectBaseDesigned as the common interface for MetaDataObject's. This class is intended as the value part of the (key,value) pair to be stored in a MetaDataDictionary
itk::MetaDTITubeConverter< NDimensions >
itk::MetaEllipseConverter< NDimensions >
itk::MetaEventEvent abstract class
itk::MetaGaussianConverter< NDimensions >
itk::MetaGroupConverter< NDimensions >
itk::MetaImageConverter< NDimensions, PixelType >
itk::MetaImageIORead MetaImage file format
itk::MetaImageIOFactoryCreate instances of MetaImageIO objects using an object factory
itk::MetaLandmarkConverter< NDimensions >
itk::MetaLineConverter< NDimensions >
itk::MetaMeshConverter< NDimensions, PixelType, TMeshTraits >
itk::MetaSceneConverter< NDimensions, PixelType, TMeshTraits >
itk::MetaSurfaceConverter< NDimensions >
itk::MetaTubeConverter< NDimensions >
itk::MetaVesselTubeConverter< NDimensions >
itk::fem::LoadBCMFC::MFCTermClass that holds information about one term in MFC constraint equation
itk::MINC2ImageIOClass that defines how to read MINC2 file format. Note,like ITK, MINC2 is N dimensional and dimensions can be submitted in any arbitrary order. Here we make sure the dimensions are ordered as xspace, yspace, zspace, time and vector_dimension and so on or xfrequencey, yfrequency, zfrequency, tfrequency and vector_dimension and so on NOTE** This class only reads the regularly sampled dimensions as I am not sure how to deal with "iregularly sampled" dimensions yet!
itk::MINC2ImageIOFactoryCreate instances of MINC2ImageIO objects using an object factory
itk::MinFunctor< TPixel >
itk::Function::Minimum< TInput1, TInput2, TOutput >
itk::Function::MinimumAccumulator< TInputPixel >
itk::MinimumDecisionRuleA Decision rule that choose the class that has minimum value
itk::Statistics::MinimumDecisionRule2A Decision rule that choose the class of which discriminant score is the largest. This class will replace the MinimumDecisionRule in Code/Common
itk::MinimumImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements a pixel-wise operator Min(a,b) between two images
itk::Functor::MinimumIndexLabelObjectAccessor< TLabelObject >
itk::Functor::MinimumLabelObjectAccessor< TLabelObject >
itk::MinimumMaximumImageCalculator< TInputImage >
itk::MinimumMaximumImageFilter< TInputImage >Computes the minimum and the maximum intensity values of an image
itk::MinimumProjectionImageFilter< TInputImage, TOutputImage >Minimum projection
itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, TFilter >A separable filter for filter which are using radius
itk::MinMaxCurvatureFlowFunction< TImage >
itk::MinMaxCurvatureFlowImageFilter< TInputImage, TOutputImage >Denoise an image using min/max curvature flow
itk::MinMeasureBoundCriterion< TMesh, TElement, TMeasure, TPriorityQueueWrapper >
itk::MinPriorityQueueElementWrapper< TElement, TElementPriority, TElementIdentifier >
itk::MIRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >
itk::MirrorPadImageFilter< TInputImage, TOutputImage >Increase the image size by padding with replicants of the input image value
itk::Statistics::MixtureModelComponentBase< TSample >Base class for distribution modules that supports analytical way to update the distribution parameters
itk::ModifiedEvent
itk::Functor::Modulus2< TInput1, TInput2, TOutput >
itk::Function::Modulus3< TInput1, TInput2, TInput3, TOutput >
itk::ModulusImageFilter< TInputImage, TOutputImage >Computes the modulus (x % dividend) pixel-wise
itk::Function::ModulusSquare3< TInput1, TInput2, TInput3, TOutput >
itk::Functor::ModulusTransform< TInput, TOutput >
itk::Function::MorphologicalGradientHistogram< TInputPixel >
itk::MorphologicalGradientImageFilter< TInputImage, TOutputImage, TKernel >Morphological gradients enhance the variation of pixel intensity in a given neighborhood
itk::MorphologicalWatershedFromMarkersImageFilter< TInputImage, TLabelImage >Morphological watershed transform from markers
itk::MorphologicalWatershedImageFilter< TInputImage, TOutputImage >TODO
itk::MorphologyHistogram< TInputPixel >
itk::Function::MorphologyHistogram< TInputPixel, TCompare >
itk::MorphologyHistogramMap< TInputPixel, TCompare >
itk::MorphologyHistogramVec< TInputPixel, TCompare >
itk::MorphologyImageFilter< TInputImage, TOutputImage, TKernel >Base class for the morphological operations such as erosion and dialation
itk::MovingHistogramDilateImageFilter< TInputImage, TOutputImage, TKernel >Gray scale dilation of an image
itk::MovingHistogramErodeImageFilter< TInputImage, TOutputImage, TKernel >Gray scale erosion of an image
itk::MovingHistogramImageFilter< TInputImage, TOutputImage, TKernel, THistogram >Implements a generic moving histogram algorithm
itk::MovingHistogramImageFilterBase< TInputImage, TOutputImage, TKernel >Implements a generic moving histogram algorithm
itk::MovingHistogramMorphologicalGradientImageFilter< TInputImage, TOutputImage, TKernel >Morphological gradients enhance the variation of pixel intensity in a given neighborhood
itk::MovingHistogramMorphologyImageFilter< TInputImage, TOutputImage, TKernel, THistogram >Base class for MovingHistogramDilateImageFilter and MovingHistogramErodeImageFilter
itk::MRASlabIdentifier< TInputImage >Identifies slab in MR images comparing minimum intensity averages
itk::MRCHeaderObjectThis class is a light wrapper for a couple of plain old data structures, so that they can be utilized in a MetaDataDictionary
itk::MRCImageIOAn ImageIO class to read the MRC file format. The MRC file format frequently has the extension ".mrc" or ".rec". It is used frequently for electron microscopy and is an emerging standard for cryo-electron tomography and molecular imaging. The format is used to represent 2D, 3D images along with 2D tilt series for tomography
itk::MRCImageIOFactoryCreate instances of MRCImageIO objects using an object factory
itk::MRFImageFilter< TInputImage, TClassifiedImage >Implementation of a labeller object that uses Markov Random Fields to classify pixels in an image data set
itk::MRIBiasEnergyFunction< TImage, TImageMask, TBiasField >Cost function for optimization
itk::MRIBiasFieldCorrectionFilter< TInputImage, TOutputImage, TMaskImage >Corrects 3D MRI bias field
itk::Function::Mult< TInput1, TInput2, TOutput >
itk::Statistics::MultilayerNeuralNetworkBase< TMeasurementVector, TTargetVector, TLearningLayer >
itk::MultiphaseDenseFiniteDifferenceImageFilter< TInputImage, TFeatureImage, TOutputImage, TFunction, TIdCell >
itk::MultiphaseFiniteDifferenceImageFilter< TInputImage, TFeatureImage, TOutputImage, TFiniteDifferenceFunction, TIdCell >
itk::MultiphaseSparseFiniteDifferenceImageFilter< TInputImage, TFeatureImage, TOutputImage, TFunction, TIdCell >This class implements a finite difference partial differential equation solver for evolving surfaces embedded in volumes as level-sets
itk::MultipleLogOutputClass MultipleLogOutput allows writing simultaneously to multiple streams. Note that the class derives from std::streambuf and contains a std::set<> of LogOutput
itk::MultipleValuedCostFunctionThis class is a base for the CostFunctions returning a multiple values
itk::MultipleValuedNonLinearOptimizerThis class is a base for the Optimization methods that optimize a multiple valued function
itk::MultipleValuedNonLinearVnlOptimizerThis class is a base for the Optimization methods that optimize a multi-valued function
itk::MultipleValuedVnlCostFunctionAdaptorThis class is an Adaptor that allows to pass itk::MultipleValuedCostFunctions to vnl_optimizers expecting a vnl_cost_function
itk::Concept::MultiplyAndAssignOperator< T1, T2 >
itk::Functor::MultiplyByConstant< TInput, TConstant, TOutput >
itk::MultiplyByConstantImageFilter< TInputImage, TConstant, TOutputImage >Multiply input pixels by a constant
itk::MultiplyImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements an operator for pixel-wise multiplication of two images
itk::Concept::MultiplyOperator< T1, T2, T3 >
itk::Statistics::MultiquadricRadialBasisFunction< ScalarType >
itk::MultiResolutionImageRegistrationMethod< TFixedImage, TMovingImage >Base class for multi-resolution image registration methods
itk::MultiResolutionPDEDeformableRegistration< TFixedImage, TMovingImage, TDeformationField, TRealType >Framework for performing multi-resolution PDE deformable registration
itk::MultiResolutionPyramidImageFilter< TInputImage, TOutputImage >Framework for creating images in a multi-resolution pyramid
itk::MultiScaleHessianBasedMeasureImageFilter< TInputImage, THessianImage, TOutputImage >A filter to enhance structures using Hessian eigensystem-based measures in a multiscale framework
itk::MultiThreaderA class for performing multithreaded execution
itk::ImageToImageMetric< TFixedImage, TMovingImage >::MultiThreaderParameterType
itk::MultivariateLegendrePolynomial2D and 3D multivariate Legendre Polynomial
itk::CellInterface< TPixelType, TCellTraits >::MultiVisitorA visitor that can visit different cell types in a mesh. CellInterfaceVisitor instances can be registered for each type of cell that needs to be visited
itk::MutexLockMutual exclusion locking class
itk::MutexLockHolder< TMutex >
itk::MutualInformationHistogramImageToImageMetric< TFixedImage, TMovingImage >Computes the mutual information between two images to be registered using the histograms of the intensities in the images. This class is templated over the type of the fixed and moving images to be compared
itk::MutualInformationImageToImageMetric< TFixedImage, TMovingImage >Computes the mutual information between two images to be registered
itk::NarrowBand< NodeType >
itk::NarrowBandCurvesLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in images based on user supplied edge potential map
itk::NarrowBandImageFilterBase< TInputImage, TOutputImage >This class implements a multi-threaded finite difference image to image solver that can be applied to an arbitrary list of pixels
itk::NarrowBandLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType, TOutputImage >A base class which defines the API for implementing a special class of image segmentation filters using level set methods
itk::NarrowBandThresholdSegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in images based on intensity values
itk::NaryAddImageFilter< TInputImage, TOutputImage >Implements an operator for pixel-wise addition of two images
itk::NaryFunctorImageFilter< TInputImage, TOutputImage, TFunction >Implements pixel-wise generic operation of Nth similar images
itk::NaryMaximumImageFilter< TInputImage, TOutputImage >Implements an operator computing the pixel-wise maximum of several images
itk::NCCRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >
itk::NearestNeighborExtrapolateImageFunction< TInputImage, TCoordRep >Nearest neighbor extrapolation of a scalar image
itk::NearestNeighborInterpolateImageFunction< TInputImage, TCoordRep >Nearest neighbor interpolation of a scalar image
itk::Statistics::KdTree< TSample >::NearestNeighborsData structure for storing k-nearest neighbor search result (k number of Neighbors)
itk::Neighborhood< TPixel, VDimension, TAllocator >A light-weight container object for storing an N-dimensional neighborhood of values
itk::NeighborhoodAccessorFunctor< TImage >Provides accessor interfaces to Get pixels and is meant to be used on pointers contained within Neighborhoods. A typical user should not need to use this class directly. This class is used by the neighborhood iterators to get pixels from pixel pointers or assign a pixel to an address
itk::NeighborhoodAllocator< TPixel >
itk::NeighborhoodBinaryThresholdImageFunction< TInputImage, TCoordRep >Determine whether all the pixels in the specified neighborhood meet a threshold criteria
itk::NeighborhoodConnectedImageFilter< TInputImage, TOutputImage >Label pixels that are connected to a seed and lie within a neighborhood
itk::NeighborhoodInnerProduct< TImage, TOperator, TComputation >
itk::NeighborhoodIterator< TImage, TBoundaryCondition >Defines iteration of a local N-dimensional neighborhood of pixels across an itk::Image
itk::NeighborhoodOperator< TPixel, VDimension, TAllocator >Virtual class that defines a common interface to all neighborhood operator subtypes
itk::NeighborhoodOperatorImageFilter< TInputImage, TOutputImage, TOperatorValueType >Applies a single NeighborhoodOperator to an image region
itk::NeighborhoodOperatorImageFunction< TInputImage, TOutput >Compute the convolution of a neighborhood operator with the image at a specific location in space, i.e. point, index or continuous index. This class is templated over the input image type
itk::Statistics::NeighborhoodSampler< TSample >Generates a Subsample that is sampled from the input sample using a spherical kernel
itk::NeuralNetworkFileReader< TNetwork >Reader for Neural Network
itk::NeuralNetworkFileWriter< TNetwork >Writer for Neural Network
itk::Statistics::NeuralNetworkObject< TMeasurementVector, TTargetVector >
itk::NiftiImageIOClass that defines how to read Nifti file format. Nifti IMAGE FILE FORMAT - As much information as I can determine from sourceforge.net/projects/Niftilib
itk::NiftiImageIOFactoryCreate instances of NiftiImageIO objects using an object factory
itk::Statistics::NNetDistanceMetricBase< TMeasurementVector >
itk::fem::Element::NodeClass that stores information required to define a node
itk::NodeList< TItemType >Stores secondary lists of nodes with pointers to the contained items
itk::NodeOfPermutation
itk::NoEvent
itk::NoiseImageFilter< TInputImage, TOutputImage >Calculate the local noise in an image
itk::NonLinearOptimizerWrap of the vnl_nonlinear_minimizer to be adapted
itk::NonThreadedShrinkImageFilter< TInputImage, TOutputImage >Reduce the size of an image by an integer factor
itk::NonUniformBSpline< TDimension >BSpline with nonuniform knot spacing
itk::NormalBandNode< TImageType >This is a data storage class that can is used as the node type for the SparseImage class
itk::NormalizedCorrelationImageFilter< TInputImage, TMaskImage, TOutputImage, TOperatorValueType >Computes the normalized correlation of an image and a template
itk::NormalizedCorrelationImageToImageMetric< TFixedImage, TMovingImage >Computes similarity between two images to be registered
itk::NormalizedCorrelationPointSetToImageMetric< TFixedPointSet, TMovingImage >Computes similarity between pixel values of a point set and intensity values of an image
itk::NormalizedMutualInformationHistogramImageToImageMetric< TFixedImage, TMovingImage >Computes normalized mutual information between two images to be registered using the histograms of the intensities in the images
itk::NormalizeImageFilter< TInputImage, TOutputImage >Normalize an image by setting its mean to zero and variance to one
itk::Statistics::NormalVariateGeneratorNormal random variate generator
itk::NormalVectorDiffusionFunction< TSparseImageType >This class defines all the necessary functionality for performing isotropic and anisotropic diffusion operations on vector neighborhoods from a sparse image
itk::NormalVectorFunctionBase< TSparseImageType >This class defines the common functionality for Sparse Image neighborhoods of unit vectors
itk::Functor::NOT< TInput, TOutput >
itk::NotImageFilter< TInputImage, TOutputImage >Implements the NOT logical operator pixel-wise on an image
itk::Concept::NotOperator< T >
itk::NrrdImageIORead and write the "Nearly Raw Raster Data" (Nrrd) image format. The Nrrd format was developed as part of the Teem package (teem.sourceforge.net)
itk::NrrdImageIOFactoryCreate instances of NrrdImageIO objects using an object factory
itk::NthElementImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the N-th element of its pixels
itk::NthElementImageAdaptorHelper< TImage, TOutputPixelType >
itk::NthElementPixelAccessor< T, TContainer >Give access to the N-th of a Container type
itk::NumberOfFacesCriterion< TMesh, TElement, TMeasure, TPriorityQueueWrapper >
itk::Functor::NumberOfLinesLabelObjectAccessor< TLabelObject >
itk::NumberOfPointsCriterion< TMesh, TElement, TMeasure, TPriorityQueueWrapper >
itk::NumericSeriesFileNamesGenerate an ordered sequence of filenames
itk::ObjectBase class for most itk classes
itk::ObjectFactory< T >Create instances of a class
itk::ObjectFactoryBaseCreate instances of classes using an object factory
itk::ObjectMorphologyImageFilter< TInputImage, TOutputImage, TKernel >Base class for the morphological operations being applied to isolated objects in an image
itk::ObjectStore< TObjectType >A specialized memory management object for allocating and destroying contiguous blocks of objects
itk::Octree< TPixel, ColorTableSize, MappingFunctionType >Represent a 3D Image with an Octree data structure
itk::OctreeBaseProvides non-templated access to templated instances of Octree
itk::OctreeNode
itk::OctreeNodeBranch
itk::Offset< VOffsetDimension >Represent the offset between two n-dimensional indexes in a n-dimensional image
itk::Functor::OffsetLexicographicCompare< VOffsetDimension >Order Offset instances lexicographically
itk::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >
itk::OnePlusOneEvolutionaryOptimizer1+1 evolutionary strategy optimizer
itk::OnesMatrixCoefficients< TInputMesh >Compute a matrix filled by 1s wherever two vertices are connected by an edge
itk::OneWayEquivalencyTableHash table to manage integral label equivalencies that are order dependent
itk::OpeningByReconstructionImageFilter< TInputImage, TOutputImage, TKernel >Opening by reconstruction of an image
itk::OptimizerGeneric representation for an optimization method
itk::Functor::OR< TInput1, TInput2, TOutput >
itk::OrientationAdapterBase< OrientationType, Dimension >Base class that converts Orientation representations to direction cosines
itk::OrientedImage< TPixel, VImageDimension >Templated n-dimensional oriented image class
itk::OrientImageFilter< TInputImage, TOutputImage >Permute axes and then flip images as needed to obtain agreement in coordinateOrientation codes
itk::OrImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements the OR logical operator pixel-wise between two images
itk::OrthogonallyCorrected2DParametricPathRepresent an orthogonally corrected 2D parametric path
itk::OrthogonalSwath2DPathFilter< TFourierSeriesPath, TSwathMeritImage >Filter that optimizes a 2D path relative to an image
itk::Concept::OStreamWritable< T >
itk::OStringStream
itk::OtsuMultipleThresholdsCalculator< TInputHistogram >Computes Otsu's thresholds for a histogram
itk::OtsuMultipleThresholdsImageFilter< TInputImage, TOutputImage >Threshold an image using multiple Otsu Thresholds
itk::OtsuThresholdImageCalculator< TInputImage >Computes the Otsu's threshold for an image
itk::OtsuThresholdImageFilter< TInputImage, TOutputImage >Threshold an image using the Otsu Threshold
itk::OutputWindowMessages sent from the system are collected by this object
itk::ObjectFactoryBase::OverrideInformationInternal implementation class for ObjectFactorBase
itk::Functor::OverUnderColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::PadImageFilter< TInputImage, TOutputImage >Increase the image size by padding. Superclass for filters that fill in extra pixels
itk::PadLabelMapFilter< TInputImage >Pad a LabelMap image
itk::par_parameter
itk::ParallelSparseFieldCityBlockNeighborList< TNeighborhoodType >A convenience class for storing indicies which reference neighbor pixels within a neighborhood
itk::ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >This class implements a finite difference partial differential equation solver for evolving surfaces embedded in volumes as level-sets
itk::ParallelSparseFieldLevelSetNode< TNodeIndexType >
itk::ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::ParallelSparseFieldLevelSetThreadStruct
itk::ParametricPath< VDimension >Represent a parametric path through ND Space
itk::ParametricSpaceToImageSpaceMeshFilter< TInputMesh, TOutputMesh >ParametricSpaceToImageSpaceMeshFilter takes an itk::Mesh on which the point Data is expected to contain itk::Index of itk::Image pixels associated with each point of the Mesh, and construct with them a new mesh whose points are in the coordinates of those pixels
itk::PasteImageFilter< TInputImage, TSourceImage, TOutputImage >Paste an image into another image
itk::Path< TInput, TOutput, VDimension >Represent a path through ND Space
itk::PathAndImageToPathFilter< TInputPath, TInputImage, TOutputPath >Base class for filters that take both a path and an image as input and produce a path as output
itk::PathConstIterator< TImage, TPath >PathConstIterator iterates (traces) over a path through an image
itk::PathIterator< TImage, TPath >PathIterator iterates (traces) over a path through an image
itk::PathSource< TOutputPath >Base class for all process objects that output path data
itk::PathToChainCodePathFilter< TInputPath, TOutputChainCodePath >Filter that produces a chain code version of a path
itk::PathToImageFilter< TInputPath, TOutputImage >Base class for filters that take a Path as input and produce an image as output. Base class for filters that take a Path as input and produce an image as output. By default, if the user does not specify the size of the output image, the maximum size of the path's bounding box is used. The default spacing of the image is given by the spacing of the input path (currently assumed internally to be 1.0)
itk::PathToPathFilter< TInputPath, TOutputPath >Base class for filters that take a path as input and produce a path as output
itk::PCAShapeSignedDistanceFunction< TCoordRep, VSpaceDimension, TImage >Compute the signed distance from a N-dimensional PCA Shape
itk::PDEDeformableRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >Deformably register two images using a PDE algorithm
itk::PDEDeformableRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >
itk::Functor::PerimeterLabelObjectAccessor< TLabelObject >
itk::PeriodicBoundaryCondition< TImage >A function object that determines values outside of image boundaries according to periodic (wrap-around) conditions
itk::PermuteAxesImageFilter< TImage >Permutes the image axes according to a user specified order
itk::PhasedArray3DSpecialCoordinatesImage< TPixel >Templated 3D nonrectilinear-coordinate image class for phased-array "range" images
itk::PhilipsPARClass for reading parameters from a Philips PAR file
itk::PhilipsRECImageIOClass that defines how to read Philips REC/PAR image files. This class supports reading only and not writing
itk::PhilipsRECImageIOFactoryCreate instances of PhilipsRECImageIO objects using an object factory
itk::Functor::PhysicalSizeLabelObjectAccessor< TLabelObject >
itk::Functor::PhysicalSizeOnBorderLabelObjectAccessor< TLabelObject >
itk::PickEvent
itk::PixelAccessor< TInternalType, TExternalType >Give access to partial aspects of a type
itk::PlaneSpatialObject< TDimension >
itk::PNGImageIOImageIO object for reading and writing PNG images
itk::PNGImageIOFactoryCreate instances of PNGImageIO objects using an object factory
itk::Point< TCoordRep, NPointDimension >A templated class holding a geometric point in n-Dimensional space
itk::Point1D
itk::PointBasedSpatialObject< TDimension >This class serves as the base class for point-based spatial objects
itk::PointLocator< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >Accelerate geometric searches for points
itk::PointSet< TPixelType, VDimension, TMeshTraits >A superclass of the N-dimensional mesh structure; supports point (geometric coordinate and attribute) definition
itk::PointSetToImageFilter< TInputPointSet, TOutputImage >Base class for filters that take a PointSet as input and produce an image as output. By default, if the user does not specify the size of the output image, the maximum size of the point-set's bounding box is used
itk::PointSetToImageMetric< TFixedPointSet, TMovingImage >Computes similarity between a point set and an image
itk::PointSetToImageRegistrationMethod< TFixedPointSet, TMovingImage >Base class for PointSet to Image Registration Methods
itk::Statistics::PointSetToListAdaptor< TPointSet >This class provides ListSampleBase interfaces to ITK PointSet
itk::Statistics::PointSetToListSampleAdaptor< TPointSet >This class provides ListSample interface to ITK PointSet
itk::PointSetToPointSetMetric< TFixedPointSet, TMovingPointSet >Computes similarity between two point sets
itk::PointSetToPointSetRegistrationMethod< TFixedPointSet, TMovingPointSet >Base class for PointSet to PointSet Registration Methods
itk::PointSetToSpatialObjectDemonsRegistration< TFixedPointSet, TMovingSpatialObject >Implementation of Demons Registration between a PointSet and a SpatialObject
itk::PolygonCell< TCellInterface >
itk::PolygonGroupSpatialObject< TDimension >Implements a Region Of Interest Type
itk::PolygonGroupSpatialObjectXMLFileReader
itk::PolygonGroupSpatialObjectXMLFileWriter
itk::PolygonSpatialObject< TDimension >TODO
itk::PolylineMask2DImageFilter< TInputImage, TPolyline, TOutputImage >Implements 2D image masking operation constrained by a contour
itk::PolylineMaskImageFilter< TInputImage, TPolyline, TVector, TOutputImage >Implements image masking operation constrained by a polyline on a plane perpendicular to certain viewing direction
itk::PolyLineParametricPath< VDimension >Represent a path of line segments through ND Space
itk::PostOrderTreeIterator< TTreeType >
itk::PowellOptimizerImplements Powell optimization using Brent line search
itk::PreOrderTreeIterator< TTreeType >
itk::Functor::PrincipalAxesLabelObjectAccessor< TLabelObject >
itk::Functor::PrincipalMomentsLabelObjectAccessor< TLabelObject >
itk::PriorityQueueContainer< TElementWrapper, TElementWrapperInterface, TElementPriority, TElementIdentifier >
itk::Statistics::ProbabilityDistributionProbabilityDistribution class defines common interface for statistical distributions (pdfs, cdfs, etc.)
itk::ProcessObjectProcessObject is the base class for all process objects (source, filters, mappers) in the Insight data processing pipeline
itk::Statistics::ProductInputFunction< TMeasurementVector, ScalarType >
itk::ProgressAccumulatorFacilitates progress reporting for filters that wrap around multiple other filters
itk::ProgressEvent
itk::ProgressReporterImplements progress tracking for a filter
itk::ProjectionImageFilter< TInputImage, TOutputImage, TAccumulator >Implements an accumulation of an image along a selected direction
Provide
itk::fftw::Proxy< TPixel >
itk::QuadEdgeBase class for the implementation of a quad-edge data structure as proposed in "Guibas and Stolfi 1985"
itk::QuadEdgeMesh< TPixel, VDimension, TTraits >Mesh class for 2D manifolds embedded in ND space
itk::QuadEdgeMeshBaseIterator< TQuadEdge >Base iterator class for QuadEdgeMesh
itk::QuadEdgeMeshBorderTransform< TInputMesh, TOutputMesh >Transform the mandatoryly unique border of an itkQE::Mesh into either a circle (conformal) or a square (arclenght-wise)
itk::QuadEdgeMeshBoundaryEdgesMeshFunction< TMesh >Build a list of references to edges (as GeometricalQuadEdge::RawPointer) each one representing a different boundary component
itk::QuadEdgeMeshCleanFilter< TInput, TOutput >
itk::QuadEdgeMeshConstFrontIterator< TMesh, TQE >Const quad edge mesh front iterator
itk::QuadEdgeMeshConstIterator< TQuadEdge >Const iterator for QuadEdgeMesh
itk::QuadEdgeMeshConstIteratorGeom< TGeometricalQuadEdge >Const geometrical iterator
itk::QuadEdgeMeshDecimationCriterion< TMesh, TElement, TMeasure, TPriorityQueueWrapper >
itk::QuadEdgeMeshDecimationFilter< TInput, TOutput, TCriterion >
itk::QuadEdgeMeshDecimationQuadricElementHelper< TPoint >TODO explicit specification for VDimension=3!!!
itk::QuadEdgeMeshDelaunayConformingFilter< TInputMesh, TOutputMesh >FIXME Add documentation
itk::QuadEdgeMeshDiscreteCurvatureEstimator< TInputMesh, TOutputMesh >FIXME
itk::QuadEdgeMeshDiscreteCurvatureTensorEstimator< TInputMesh, TOutputMesh >FIXME Add documentation here
itk::QuadEdgeMeshDiscreteGaussianCurvatureEstimator< TInputMesh, TOutputMesh >See the following paper title: Discrete Differential-Geometry Operators for Triangulated 2-Manifolds authors: Mark Meyer, Mathieu Desbrun, Peter Schroder, Alan H. Barr conference: VisMath '02 location: Berlin (Germany)
itk::QuadEdgeMeshDiscreteMaxCurvatureEstimator< TInputMesh, TOutputMesh >FIXME Add documentation here
itk::QuadEdgeMeshDiscreteMeanCurvatureEstimator< TInputMesh, TOutputMesh >See the following paper title: Discrete Differential-Geometry Operators for Triangulated 2-Manifolds authors: Mark Meyer, Mathieu Desbrun, Peter Schroder, Alan H. Barr conference: VisMath '02 location: Berlin (Germany)
itk::QuadEdgeMeshDiscreteMinCurvatureEstimator< TInputMesh, TOutputMesh >FIXME add documentation here
itk::QuadEdgeMeshDiscretePrincipalCurvaturesEstimator< TInputMesh, TOutputMesh >FIXME add documentation here
itk::QuadEdgeMeshEdgeMergeDecimationFilter< TInput, TOutput, TCriterion >
itk::QuadEdgeMeshEulerOperatorCreateCenterVertexFunction< TMesh, TQEType >
itk::QuadEdgeMeshEulerOperatorDeleteCenterVertexFunction< TMesh, TQEType >
itk::QuadEdgeMeshEulerOperatorFlipEdgeFunction< TMesh, TQEType >
itk::QuadEdgeMeshEulerOperatorJoinFacetFunction< TMesh, TQEType >
itk::QuadEdgeMeshEulerOperatorJoinVertexFunction< TMesh, TQEType >
itk::QuadEdgeMeshEulerOperatorSplitEdgeFunction< TMesh, TQEType >
itk::QuadEdgeMeshEulerOperatorSplitFacetFunction< TMesh, TQEType >
itk::QuadEdgeMeshEulerOperatorSplitVertexFunction< TMesh, TQEType >
itk::QuadEdgeMeshExtendedTraits< TPixelType, VPointDimension, VMaxTopologicalDimension, TCoordRep, TInterpolationWeightType, TCellPixelType, TPData, TDData >Extended traits for a itkQE::Mesh
itk::QuadEdgeMeshFrontBaseIterator< TMesh, TQE >Front iterator on Mesh class
itk::QuadEdgeMeshFrontIterator< TMesh, TQE >Non const quad edge front iterator
itk::QuadEdgeMeshFunctionBase< TMesh, TOutput >
itk::QuadEdgeMeshIterator< TQuadEdge >Non const iterator for QuadMesh
itk::QuadEdgeMeshIteratorGeom< TGeometricalQuadEdge >Non const geometrical iterator
itk::QuadEdgeMeshLineCell< TCellInterface >Class that connects the QuadEdgeMesh with the Mesh
itk::QuadEdgeMeshParam< TInputMesh, TOutputMesh, TSolverTraits >Compute a planar parameterization of the input mesh
itk::QuadEdgeMeshPoint< TCoordRep, VPointDimension, TQuadEdge >Wrapper around a itk::Point in order to add a reference to an entry in the edge ring
itk::QuadEdgeMeshPolygonCell< TCellInterface >
itk::QuadEdgeMeshQuadricDecimation< TInput, TOutput, TCriterion >
QuadEdgeMeshScalarDataVTKPolyDataThis class saves a QuadMesh into a VTK-legacy file format, including its scalar data associated with points
itk::QuadEdgeMeshScalarDataVTKPolyDataWriter< TMesh >
itk::QuadEdgeMeshSmoothing< TInputMesh, TOutputMesh >Quad Edge Mesh Smoothing Filter
itk::QuadEdgeMeshSquaredEdgeLengthDecimation< TInput, TOutput, TCriterion >
itk::QuadEdgeMeshTopologyChecker< TMesh >Make some basic checks in order to verify that the considered mesh is not degenerated and correctly represents a surface with a potential boundary
itk::QuadEdgeMeshToQuadEdgeMeshFilter< TInputMesh, TOutputMesh >Duplicates the content of a Mesh
itk::QuadEdgeMeshTraits< TPixel, VPointDimension, TPData, TDData, TCoordRep, TInterpolationWeight >Class holding the traits of the QuadEdgeMesh
itk::QuadEdgeMeshZipMeshFunction< TMesh, TQEType >
itk::QuadraticEdgeCell< TCellInterface >
itk::QuadraticTriangleCell< TCellInterface >
itk::QuadraticTriangleCellTopology
itk::QuadrilateralCell< TCellInterface >
itk::QuadrilateralCellTopology
itk::QuaternionOrientationAdapter< VDimension >Converts QuaternionOrientation flags to/from direction cosines
itk::QuaternionRigidTransform< TScalarType >QuaternionRigidTransform of a vector space (e.g. space coordinates)
itk::QuaternionRigidTransformGradientDescentOptimizerImplement a gradient descent optimizer
itk::Statistics::QuickPropLearningRule< LayerType, TTargetVector >
itk::Statistics::RadialBasisFunctionBase< ScalarType >
itk::RandomImageSource< TOutputImage >Generate an n-dimensional image of random pixel values
itk::RandomPermutation
itk::Statistics::RandomVariateGeneratorBaseThis class defines common interfaces for random variate generators
itk::RankHistogram< TInputPixel >
itk::RankHistogramMap< TInputPixel, TCompare >
itk::RankHistogramVec< TInputPixel, TCompare >
itk::RankImageFilter< TInputImage, TOutputImage, TKernel >Rank filter of a greyscale image
itk::RawImageIO< TPixel, VImageDimension >Read and write raw binary images
itk::RawImageIOFactory< TPixel, VImageDimension >
itk::RayCastInterpolateImageFunction< TInputImage, TCoordRep >Projective interpolation of an image at specified positions
itk::Statistics::RBFBackPropagationLearningFunction< LayerType, TTargetVector >
itk::Statistics::RBFLayer< TMeasurementVector, TTargetVector >
itk::Statistics::RBFNetwork< TMeasurementVector, TTargetVector >
itk::fem::ReadInfoTypeHelper class for storing additional information that is required when reading FEM objects from stream
itk::Functor::RealAndImaginaryToComplex< TInput1, TInput2, TOutput >
itk::RealAndImaginaryToComplexImageFilter< TInputPixel1, TInputPixel2, TOutputPixel, NDimension >Implements pixel-wise conversion of real and imaginar data into complex voxels
itk::RealTimeClockThe RealTimeClock provides a timestamp from a real-time clock
itk::ReceptorMemberCommand< T >Command subclass that calls a pointer to a member function
itk::ReconstructionByDilationImageFilter< TInputImage, TOutputImage >Grayscale reconstruction by dilation of an image
itk::ReconstructionByErosionImageFilter< TInputImage, TOutputImage >Grayscale reconstruction by erosion of an image
itk::ReconstructionImageFilter< TInputImage, TOutputImage, TCompare >Performs a grayscale geodesic reconstruction -- for performance comparison with GrayscaleGeodesicDilateImageFilter
itk::RecursiveGaussianImageFilter< TInputImage, TOutputImage >Base class for computing IIR convolution with an approximation of a Gaussian kernel
itk::RecursiveMultiResolutionPyramidImageFilter< TInputImage, TOutputImage >Creates a multi-resolution pyramid using a recursive implementation
itk::RecursiveSeparableImageFilter< TInputImage, TOutputImage >Base class for recursive convolution with a kernel
itk::Functor::RedColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::RedPixelAccessor< T >Give access to the red component of a RGBPixel type
itk::ReflectImageFilter< TInputImage, TOutputImage >Implements a Reflection of an image along a selected direction
itk::ReflectiveImageRegionConstIterator< TImage >Multi-dimensional image iterator which only walks a region
itk::ReflectiveImageRegionIterator< TImage >Multi-dimensional image iterator which only walks a region
itk::RegionA region represents some portion or piece of data
itk::RegionalMaximaImageFilter< TInputImage, TOutputImage >Produce a binary image where foreground is the regional maxima of the input image
itk::RegionalMinimaImageFilter< TInputImage, TOutputImage >Produce a binary image where foreground is the regional minima of the input image
itk::RegionBasedLevelSetFunction< TInput, TFeature, TSharedData >LevelSet function that computes a speed image based on regional integrals
itk::RegionBasedLevelSetFunctionData< TInputImage, TFeatureImage >Helper class used to share data in the ScalarChanAndVeseLevelSetFunction
itk::RegionBasedLevelSetFunctionSharedData< TInputImage, TFeatureImage, TSingleData >Helper class used to share data in the ScalarChanAndVeseLevelSetFunction
itk::Functor::RegionElongationLabelObjectAccessor< TLabelObject >
itk::RegionFromReferenceLabelMapFilter< TInputImage >Set the region from a reference image
itk::RegionGrowImageFilter< TInputImage, TOutputImage >Base class for RegionGrowImageFilter object
itk::Functor::RegionLabelObjectAccessor< TLabelObject >
itk::RegionOfInterestImageFilter< TInputImage, TOutputImage >Extract a region of interest from the input image
itk::NarrowBand< NodeType >::RegionStruct
itk::SparseFieldLayer< TNodeType >::RegionType
itk::RegularExpressionSeriesFileNamesGenerate an ordered sequence of filenames that match a regular expression
itk::RegularizedHeavisideStepFunction< TInput, TOutput >Base class of the Regularized (smoothed) Heaviside functions
itk::RegularSphereMeshSource< TOutputMesh >Inputs are the center of the mesh, the scale (radius in each dimension) of the mesh and a resolution parameter, which corresponds to the recursion depth whlie creating a spherical triangle mesh
itk::RegularStepGradientDescentBaseOptimizerImplement a gradient descent optimizer
itk::RegularStepGradientDescentOptimizerImplement a gradient descent optimizer
itk::ReinitializeLevelSetImageFilter< TLevelSet >Reinitialize the level set to the signed distance function
itk::RelabelComponentImageFilter< TInputImage, TOutputImage >Relabel the components in an image such that consecutive labels are used
itk::RelabelComponentImageFilter< TInputImage, TOutputImage >::RelabelComponentObjectType
itk::RelabelComponentImageFilter< TInputImage, TOutputImage >::RelabelComponentSizeInPixelsComparator
itk::watershed::Relabeler< TScalarType, TImageDimension >
itk::RelabelLabelMapFilter< TImage >This filter relabels the LabelObjects; the new labels are arranged consecutively with consideration for the background value
itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >Resample an image via a coordinate transform
itk::RescaleIntensityImageFilter< TInputImage, TOutputImage >Applies a linear transformation to the intensity levels of the input Image
itk::ResourceProbe< ValueType, MeanType >Class for computing the change of a value between two points in the code
itk::ResourceProbesCollectorBase< TProbe >Class for aggregating a set of probes
itk::FixedArray< TValueType, VLength >::ReverseIteratorA reverse iterator through the array
itk::RGBAPixel< TComponent >Represent Red, Green, Blue cand Alpha component for color images
itk::RGBGibbsPriorFilter< TInputImage, TClassifiedImage >RGBGibbsPriorFilter applies Gibbs Prior model for the segmentation of MRF images. The core of the method is based on the minimization of a Gibbsian energy function. This energy function f can be divided into three part: f = f_1 + f_2 + f_3; f_1 is related to the object homogeneity, f_2 is related to the boundary smoothness, f_3 is related to the constraint of the observation (or the noise model). The two force components f_1 and f_3 are minimized by the GradientEnergy method while f_2 is minized by the GibbsTotalEnergy method
itk::RGBPixel< TComponent >Represent Red, Green and Blue component for color images
itk::Function::RGBToLuminance< TInput, TOutput >
itk::RGBToLuminanceImageAdaptor< TImage, TOutputPixelType >Presents a color image as being composed of the Luminance of its pixels
itk::RGBToLuminanceImageFilter< TInputImage, TOutputImage >Converts an RGB image into a grayscale image
itk::Accessor::RGBToLuminancePixelAccessor< TInternalType, TExternalType >Give access to Luminance of a color pixel type
itk::RGBToVectorImageAdaptor< TImage >Presents an image of pixel type RGBPixel as being and image of Vectors
itk::Accessor::RGBToVectorPixelAccessor< T >Give access to a RGBPixel as if it were a Vector type
itk::Rigid2DTransform< TScalarType >Rigid2DTransform of a vector space (e.g. space coordinates)
itk::Rigid3DPerspectiveTransform< TScalarType >Rigid3DTramsform of a vector space (e.g. space coordinates)
itk::Rigid3DTransform< TScalarType >Rigid3DTransform of a vector space (e.g. space coordinates)
itk::RobustAutomaticThresholdCalculator< TInputImage, TGradientImage >Compute the robust automatic threshold
itk::RobustAutomaticThresholdImageFilter< TInputImage, TGradientImage, TOutputImage >Threshold an image using robust automatic threshold selection (RATS) method
itk::RootTreeIterator< TTreeType >
itk::Functor::RoundnessLabelObjectAccessor< TLabelObject >
itk::Concept::SameDimension< D1, D2 >
itk::Concept::SameDimensionOrMinusOne< D1, D2 >
itk::Concept::SameType< T1, T2 >
itk::Statistics::Sample< TMeasurementVector >A collection of measurements for statistical analysis
itk::Statistics::SampleAlgorithmBase< TInputSample >This class is a base class for algorithms that operate on Sample data. The class is templated over the SampleType, which it takes as input using the SetInputSample() method. Derived classes that operate or calculate statistics on this input sample data and can access it using the GetInputSample() method
itk::Statistics::SampleClassifier< TSample >Integration point for MembershipCalculator, DecisionRule, and target sample data
itk::Statistics::SampleClassifierFilter< TSample >Sample classification class
itk::Statistics::SampleClassifierWithMask< TSample, TMaskSample >Integration point for MembershipCalculator, DecisionRule, and target sample data. This class is functionally identical to the SampleClassifier, except that users can perform only part of the input sample that belongs to the subset of classes
itk::Statistics::SampleMeanShiftBlurringFilter< TSample >This filter blurs the input sample data using mean shift algorithm
itk::Statistics::SampleMeanShiftClusteringFilter< TSample >This filter create a cluster map from an input sample
itk::Statistics::SampleSelectiveMeanShiftBlurringFilter< TSample >This filter blurs the input sample data using mean shift algorithm selectively
itk::Statistics::SampleToHistogramFilter< TSample, THistogram >Computes the Histogram corresponding to a Sample
itk::Statistics::SampleToHistogramProjectionFilter< TInputSample, THistogramMeasurement >Projects measurement vectors on to an axis to generate an 1D histogram
itk::Statistics::SampleToSubsampleFilter< TSample >Base class of filters intended to select subsamples from samples
itk::ScalableAffineTransform< TScalarType, NDimensions >Affine transformation with a specified center of rotation
itk::ScalarAnisotropicDiffusionFunction< TImage >
itk::ScalarChanAndVeseDenseLevelSetImageFilter< TInputImage, TFeatureImage, TOutputImage, TFunction, TSharedData >Dense implementation of the Chan and Vese multiphase level set image filter
itk::ScalarChanAndVeseLevelSetFunction< TInputImage, TFeatureImage, TSharedData >LevelSet function that computes a speed image based on regional integrals of probabilities
itk::ScalarChanAndVeseLevelSetFunctionData< TInputImage, TFeatureImage >Helper class used to share data in the ScalarChanAndVeseLevelSetFunction
itk::ScalarChanAndVeseSparseLevelSetImageFilter< TInputImage, TFeatureImage, TOutputImage, TFunction, TSharedData, TIdCell >Sparse implementation of the Chan and Vese multiphase level set image filter
itk::ScalarConnectedComponentImageFilter< TInputImage, TOutputImage, TMaskImage >A connected components filter that labels the objects in an arbitrary image. Two pixels are similar if they are within threshold of each other. Uses ConnectedComponentFunctorImageFilter
itk::ScalarImageKmeansImageFilter< TInputImage, TOutputImage >Classifies the intensity values of a scalar image using the K-Means algorithm
itk::Statistics::ScalarImageTextureCalculator< TImageType, THistogramFrequencyContainer >This class computes texture descriptions from an image
itk::Statistics::ScalarImageToCooccurrenceListSampleFilter< TImage >Converts pixel data into a list of pairs in order to compute a cooccurrence Histogram
itk::Statistics::ScalarImageToCooccurrenceMatrixFilter< TImageType, THistogramFrequencyContainer >This class computes a co-occurence matrix (histogram) from a given image and a mask image if provided. Coocurrence matrces are used for image texture description
itk::Statistics::ScalarImageToGreyLevelCooccurrenceMatrixGenerator< TImageType, THistogramFrequencyContainer >This class computes a grey-level co-occurence matrix (histogram) from a given image. GLCM's are used for image texture description
itk::Statistics::ScalarImageToHistogramGenerator< TImageType >TODO
itk::Statistics::ScalarImageToListAdaptor< TImage >This class provides ListSampleBase interfaces to ITK Image
itk::Statistics::ScalarImageToTextureFeaturesFilter< TImageType, THistogramFrequencyContainer >This class computes texture descriptions from an image
itk::ScalarRegionBasedLevelSetFunction< TInputImage, TFeatureImage, TSharedData >LevelSet function that computes a speed image based on regional integrals
itk::ScalarToArrayCastImageFilter< TInputImage, TOutputImage >Creates the output image with vector type pixels filled with the intensity values from one or more input images with scalar pixels
itk::ScalarToRGBColormapImageFilter< TInputImage, TOutputImage >Implements pixel-wise intensity->rgb mapping operation on one image
itk::Functor::ScalarToRGBPixelFunctor< TScalar >Function object which maps a scalar value into an RGB pixel value
itk::ScalarVector< TScalar, TVector, TVectorDimension >A templated class holding bot scalar and vector values and responding to the GetScalar() and GetVector() methods
itk::ScaleLogarithmicTransform< TScalarType, NDimensions >Logarithmic Scale transformation of a vector space (e.g. space coordinates)
itk::ScaleSkewVersor3DTransform< TScalarType >ScaleSkewVersor3DTransform of a vector space (e.g. space coordinates)
itk::ScaleTransform< TScalarType, NDimensions >Scale transformation of a vector space (e.g. space coordinates)
itk::ScaleVersor3DTransform< TScalarType >This transform applies a Versor rotation, translation and anisotropic scale to the space
itk::ScatterMatrixImageFunction< TInputImage, TCoordRep >Calculate the scatter matrix in the neighborhood of a pixel in a Vector image
itk::SceneSpatialObject< TSpaceDimension >SceneSpatialObject has a list of SpatialObjects
itk::SecondaryNodeList< TItemType, VCliqueSize >Stores corresponding lists of nodes with pointers to the contained items
itk::watershed::SegmentTable< TScalarType >::segment_t
itk::SegmentationBorderBase class for SegmentationBorder object
itk::SegmentationLevelSetFunction< TImageType, TFeatureImageType >
itk::SegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >A base class which defines the API for implementing a special class of image segmentation filters using level set methods
itk::SegmentationRegionBase class for SegmentationRegion object
itk::watershed::Segmenter< TInputImage >
itk::watershed::SegmentTable< TScalarType >
itk::watershed::SegmentTree< TScalarType >
itk::watershed::SegmentTreeGenerator< TScalarType >
itk::Statistics::SelectiveSubsampleGenerator< TInputSample, TClassMaskSample >SelectiveSubsampleGenerator generates a Subsample object that includes measurement vectors that belong to the classes that are specified by the SetSelectedClassLabels method
itk::SemaphoreThe semaphore class is used to synchronize execution between threads
itk::ShapeDetectionLevelSetFunction< TImageType, TFeatureImageType >This function is used in the ShapeDetectionLevelSetImageFilter to segment structures in an image based on a user supplied edge potential map
itk::ShapeDetectionLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in images based on a user supplied edge potential map
itk::ShapedFloodFilledFunctionConditionalConstIterator< TImage, TFunction >Iterates over a flood-filled spatial function
itk::ShapedFloodFilledImageFunctionConditionalConstIterator< TImage, TFunction >Iterates over a flood-filled image function
itk::ShapedFloodFilledImageFunctionConditionalIterator< TImage, TFunction >Iterates over a flood-filled image function
itk::ShapedNeighborhoodIterator< TImage, TBoundaryCondition >A neighborhood iterator which can take on an arbitrary shape
itk::ShapeKeepNObjectsLabelMapFilter< TImage >Keep N objects according to their shape attributes
itk::ShapeLabelMapFilter< TImage, TLabelImage >The valuator class for the ShapeLabelObject
itk::ShapeLabelObject< TLabel, VImageDimension >A Label object to store the common attributes related to the shape of the object
itk::ShapeOpeningLabelMapFilter< TImage >Remove objects according to the value of their shape attribute
itk::ShapePriorSegmentationLevelSetFunction< TImageType, TFeatureImageType >::ShapePriorGlobalDataStruct
itk::ShapePriorMAPCostFunction< TFeatureImage, TOutputPixel >Represents the maximum aprior (MAP) cost function used ShapePriorSegmentationLevelSetImageFilter to estimate the shape paramaeters
itk::ShapePriorMAPCostFunctionBase< TFeatureImage, TOutputPixel >Represents the base class of maximum aprior (MAP) cost function used ShapePriorSegmentationLevelSetImageFilter to estimate the shape paramaeters
itk::ShapePriorSegmentationLevelSetFunction< TImageType, TFeatureImageType >This function is used in ShapePriorSegmentationLevelSetFilter to segment structures in an image based on user supplied edge potential map and shape model
itk::ShapePriorSegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >A base class which defines the API for implementing a level set segmentation filter with statistical shape influence
itk::ShapeRelabelImageFilter< TInputImage >Relabel objects according to their shape attributes
itk::ShapeRelabelLabelMapFilter< TImage >Relabels objects according to their shape attributes
itk::ShapeSignedDistanceFunction< TCoordRep, VSpaceDimension >Base class for functions which evaluates the signed distance from a shape
itk::ShapeUniqueLabelMapFilter< TImage >Remove some pixels in the label object according to the value of their shape attribute to ensure that a pixel is not in to objects
itk::ShiftScaleImageFilter< TInputImage, TOutputImage >Shift and scale the pixels in an image
itk::ShiftScaleInPlaceImageFilter< TInputImage >Shift and scale the pixels in an image
itk::ShiftScaleLabelMapFilter< TImage >Shifts and scales a label map filter, giving the option to change the background value
itk::ShrinkImageFilter< TInputImage, TOutputImage >Reduce the size of an image by an integer factor in each dimension
itk::SiemensVisionImageIOClass that defines how to read SiemensVision file format
itk::SiemensVisionImageIOFactoryCreate instances of SiemensVisionImageIO objects using an object factory
itk::Functor::SigmaLabelObjectAccessor< TLabelObject >
itk::Function::Sigmoid< TInput, TOutput >
itk::SigmoidImageFilter< TInputImage, TOutputImage >Computes the sigmoid function pixel-wise
itk::Statistics::SigmoidTransferFunction< ScalarType >
itk::Concept::Signed< T >
itk::SignedDanielssonDistanceMapImageFilter< TInputImage, TOutputImage >
itk::Statistics::SignedHardLimitTransferFunction< ScalarType >
itk::SignedMaurerDistanceMapImageFilter< TInputImage, TOutputImage >This filter calculates the squared Euclidean distance transform of a binary image in linear time for arbitrary dimensions
itk::Similarity2DTransform< TScalarType >Similarity2DTransform of a vector space (e.g. space coordinates)
itk::Similarity3DTransform< TScalarType >Similarity3DTransform of a vector space (e.g. space coordinates)
itk::SimilarityIndexImageFilter< TInputImage1, TInputImage2 >Measures the similarity between the set of non-zero pixels of two images
itk::Functor::SimilarPixelsFunctor< TInput >
itk::Functor::SimilarVectorsFunctor< TInput >A connected components filter that labels the objects in a vector image. Two vectors are pointing similar directions if one minus their dot product is less than a threshold. Vectors that are 180 degrees out of phase are similar. Assumes that vectors are normalized
itk::SimpleConstMemberCommand< T >Command subclass that calls a pointer to a member function
itk::SimpleContourExtractorImageFilter< TInputImage, TOutputImage >Computes an image of contours from
itk::SimpleDataObjectDecorator< T >Decorates any "simple" data type (data types without smart pointers) with a DataObject API
itk::SimpleFastMutexLockCritical section locking class that can be allocated on the stack
itk::SimpleFilterWatcherSimple mechanism for monitoring the pipeline events of a filter and reporting these events to std::cout
itk::MultivariateLegendrePolynomial::SimpleForwardIteratorIterator which only supports forward iteration and Begin(), IsAtEnd(), and Get() method which work just like as SimpleImageRegionIterator
itk::SimpleFuzzyConnectednessImageFilterBase< TInputImage, TOutputImage >Base class for FuzzyConnectednessImageFilter object
itk::SimpleFuzzyConnectednessRGBImageFilter< TInputImage, TOutputImage >Perform segmentation on RGB images using method of fuzzy connectedness
itk::SimpleFuzzyConnectednessScalarImageFilter< TInputImage, TOutputImage >Perform segmentation on grayscale images using method of fuzzy connectedness
itk::SimpleMemberCommand< T >Command subclass that calls a pointer to a member function
itk::SimpleMutexLockSimple mutual exclusion locking class
itk::SimplexMeshVolumeCalculator< TInputMesh >::SimplexCellVisitor
itk::SimplexMeshToTriangleMeshFilter< TInputMesh, TOutputMesh >::SimplexCellVisitor
itk::SimplexMeshAdaptTopologyFilter< TInputMesh, TOutputMesh >::SimplexCellVisitor
itk::SimplexMesh< TPixelType, VDimension, TMeshTraits >The class represents a 2-simplex mesh
itk::SimplexMeshAdaptTopologyFilter< TInputMesh, TOutputMesh >This filter changes the topology of a 2-simplex mesh
itk::SimplexMeshGeometryHandle geometric properties for vertices of a simplx mesh
itk::SimplexMeshToTriangleMeshFilter< TInputMesh, TOutputMesh >This filter converts a 2-simplex mesh into a triangle mesh
itk::SimplexMeshVolumeCalculator< TInputMesh >Adapted from itkSimplexMeshToTriangleFilter to calculate the volume of a simplex mesh using the barycenters and normals. call Compute() to calculate the volume and GetVolume() to get the value. For an example see itkDeformableSimplexMesh3DFilter.cxx (Thomas Boettger. Division Medical and Biological Informatics, German Cancer Research Center, Heidelberg.)
itk::Function::Sin< TInput, TOutput >
itk::SingleValuedCostFunctionThis class is a base for the CostFunctions returning a single value
itk::SingleValuedNonLinearOptimizerThis class is a base for the Optimization methods that optimize a single valued function
itk::SingleValuedNonLinearVnlOptimizerThis class is a base for the Optimization methods that optimize a single valued function
itk::SingleValuedVnlCostFunctionAdaptorThis class is an Adaptor that allows to pass itk::SingleValuedCostFunctions to vnl_optimizers expecting a vnl_cost_function
itk::SinImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_sin() of its pixels
itk::SinImageFilter< TInputImage, TOutputImage >Computes the vcl_sin(x) pixel-wise
itk::Accessor::SinPixelAccessor< TInternalType, TExternalType >Give access to the vcl_sin() function of a value
itk::SinRegularizedHeavisideStepFunction< TInput, TOutput >Sin-based implementation of the Regularized (smoothed) Heaviside functions
itk::Size< VDimension >Represent the size (bounds) of a n-dimensional image
itk::Functor::SizeLabelObjectAccessor< TLabelObject >
itk::Functor::SizeOnBorderLabelObjectAccessor< TLabelObject >
itk::Functor::SizeRegionRatioLabelObjectAccessor< TLabelObject >
itk::Functor::SkewnessLabelObjectAccessor< TLabelObject >
itk::SliceBySliceImageFilter< TInputImage, TOutputImage, TInputFilter, TOutputFilter, TInternalInputImage, TInternalOutputImage >Apply a filter or a pipeline slice by slice on an image
itk::SliceIterator< TPixel, TContainer >A flexible iterator for itk containers(i.e. itk::Neighborhood) that support pixel access through operator[]
itk::SmapsData_2_6Read a smaps stream and return the memory usage information. Smaps files have been added since the linux kernel 2.6
itk::SmapsFileParser< TSmapsDataType >Read a smap file (typically located in /proc/PID/smaps) and extract the memory usage information. Any smaps data reader can be used in template as long as they implement a operator>>(istream&) and have GetXXXUsage() methods
itk::SmapsRecord
itk::SmartPointer< TObjectType >Implements transparent reference counting
itk::SmartPointerForwardReference< T >Implements transparent reference counting in situations where forward references / cyclic include dependencies are a problem
itk::SmoothingRecursiveGaussianImageFilter< TInputImage, TOutputImage >Computes the smoothing of an image by convolution with the Gaussian kernels implemented as IIR filters
itk::SobelEdgeDetectionImageFilter< TInputImage, TOutputImage >A 2D or 3D edge detection using the Sobel operator
itk::SobelOperator< TPixel, VDimension, TAllocator >A NeighborhoodOperator for performing a directional Sobel edge-detection operation * at a pixel location
itk::fem::SolutionProvides functions to access the values of the solution vector
itk::fem::SolverMain FEM solver
itk::fem::SolverCrankNicolsonFEM Solver for time dependent problems; uses Crank-Nicolson implicit discretization scheme
itk::fem::SolverHyperbolicSolver class suitable for hyperbolic problems
itk::watershed::SegmentTree< TScalarType >::sort_comp
itk::MultiphaseSparseFiniteDifferenceImageFilter< TInputImage, TFeatureImage, TOutputImage, TFunction, TIdCell >::SparseDataStruct
itk::SparseFieldCityBlockNeighborList< TNeighborhoodType >A convenience class for storing indicies which reference neighbor pixels within a neighborhood
itk::SparseFieldFourthOrderLevelSetImageFilter< TInputImage, TOutputImage >This class implements the fourth order level set PDE framework
itk::SparseFieldLayer< TNodeType >
itk::SparseFieldLayerIterator< TNodeType >
itk::SparseFieldLevelSetImageFilter< TInputImage, TOutputImage >This class implements a finite difference partial differential equation solver for evolving surfaces embedded in volumes as level-sets
itk::SparseFieldLevelSetNode< TValueType >
itk::Statistics::SparseFrequencyContainerHis class is a container for an histogram
itk::Statistics::SparseFrequencyContainer2His class is a container for an histogram
itk::SparseImage< TNode, VImageDimension >This class implements a storage type for sparse image data
itk::SpatialFunction< TOutput, VImageDimension, TInput >N-dimensional spatial function class
itk::SpatialFunctionImageEvaluatorFilter< TSpatialFunction, TInputImage, TOutputImage >Evaluates a SpatialFunction onto a source image
itk::SpatialObject< TDimension >Implementation of the composite pattern
itk::SpatialObjectDuplicator< TInputSpatialObject >
itk::SpatialObjectFactory< T >Create instances of SpatialObjects
itk::SpatialObjectFactoryBaseCreate instances of SpatialObjects
itk::SpatialObjectPoint< TPointDimension >Point used for spatial objets
itk::SpatialObjectProperty< TComponentType >
itk::SpatialObjectReader< NDimensions, PixelType, TMeshTraits >TODO
itk::SpatialObjectToImageFilter< TInputSpatialObject, TOutputImage >Base class for filters that take a SpatialObject as input and produce an image as output. By default, if the user does not specify the size of the output image, the maximum size of the object's bounding box is used. The spacing of the image is given by the spacing of the input Spatial object
itk::SpatialObjectToImageStatisticsCalculator< TInputImage, TInputSpatialObject, TSampleDimension >
itk::SpatialObjectToPointSetFilter< TInputSpatialObject, TOutputPointSet >Base class for filters that take a SpatialObject as input and produce a PointSet as output. The pointset created is in physical space
itk::SpatialObjectTreeContainer< TDimension >Array class with size defined at construction time
itk::SpatialObjectTreeNode< TDimension >TODO
itk::SpatialObjectWriter< NDimensions, PixelType, TMeshTraits >TODO
itk::SpatialOrientationAdapterConverts SpatialOrientation flags to/from direction cosines
itk::SpecialCoordinatesImage< TPixel, VImageDimension >Templated n-dimensional nonrectilinear-coordinate image base class
itk::SphereMeshSource< TOutputMesh >Input the center and resolutions in 2 directions(verizon and horizon) to create a sphere-like deformable model. The cell on the surface is in the shape of triangular. More parameters are added to make the sphere mesh have global and local deform ability
itk::SphereSignedDistanceFunction< TCoordRep, VSpaceDimension >Compute the signed distance from a N-dimensional sphere
itk::SphereSpatialFunction< VImageDimension, TInput >Spatial function implementation of a sphere
itk::Functor::SpringColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::SPSAOptimizerAn optimizer based on simultaneous perturbation..
itk::Function::Sqrt< TInput, TOutput >
itk::SqrtImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_sqrt() of its pixels
itk::SqrtImageFilter< TInputImage, TOutputImage >Computes the vcl_sqrt(x) pixel-wise
itk::Accessor::SqrtPixelAccessor< TInternalType, TExternalType >Give access to the vcl_sqrt() function of a value
itk::Function::Square< TInput, TOutput >
itk::Functor::SquaredDifference2< TInput1, TInput2, TOutput >
itk::Statistics::SquaredDifferenceErrorFunction< TMeasurementVector, ScalarType >
itk::SquaredDifferenceImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements pixel-wise the computation of squared difference
itk::SquareImageFilter< TInputImage, TOutputImage >Computes the square of the intensity values pixel-wise
itk::Function::StandardDeviationAccumulator< TInputPixel, TAccumulate >
itk::Statistics::StandardDeviationPerComponentSampleFilter< TSample >Calculates the covariance matrix of the target sample data
itk::StandardDeviationProjectionImageFilter< TInputImage, TOutputImage, TAccumulate >Mean projection
itk::STAPLEImageFilter< TInputImage, TOutputImage >The STAPLE filter implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations
itk::StartEvent
itk::StartPickEvent
itk::StatisticsImageFilter< TInputImage >Compute min. max, variance and mean of an Image
itk::StatisticsKeepNObjectsLabelMapFilter< TImage >Keep N objects according to their statistics attributes
itk::StatisticsLabelMapFilter< TImage, TFeatureImage >The valuator class for the ShapeLabelObject
itk::StatisticsLabelObject< TLabel, VImageDimension >A Label object to store the common attributes related to the statistics of the object
itk::StatisticsOpeningLabelMapFilter< TImage >Remove the objects according to the value of their statistics attribute
itk::StatisticsRelabelImageFilter< TInputImage, TFeatureImage >Relabel objects according to their shape attributes
itk::StatisticsRelabelLabelMapFilter< TImage >Relabel objects according to their shape attributes
itk::StatisticsUniqueLabelMapFilter< TImage >Remove some pixels in the label object according to the value of their statistics attribute to ensure that a pixel is not in to objects
itk::StdStreamLogOutputClass StdStreamLogOutput represents a standard stream output stream. This class provides thread safety for the standard stream output stream
itk::StimulateImageIOImageIO class for reading SDT/SPR (Stimulate) images This format is similar to a MetaImageIO file: The user should specify the .spr file (not the data file : .sdt)
itk::StimulateImageIOFactoryCreate instances of StimulateImageIO objects using an object factory
itk::STLConstContainerAdaptor< TContainer >
itk::STLContainerAdaptor< TContainer >
itk::StochasticFractalDimensionImageFilter< TInputImage, TMaskImage, TOutputImage >This filter computes the stochastic fractal dimension of the input image
itk::StreamingImageFilter< TInputImage, TOutputImage >Pipeline object to control data streaming for large data processing
itk::StreamingImageIOBaseA base class for specific ImageIO file formats which support streaming
itk::StructHashFunction< TInput >Generic hash function for an arbitrary struct (or class)
itk::Function::Sub2< TInput1, TInput2, TOutput >
itk::Statistics::Subsample< TSample >This class stores a subset of instance identifiers from another sample object. You can create a subsample out of another sample object or another subsample object. The class is useful when storing or extracting a portion of a sample object. Note that when the elements of a subsample are sorted, the instance identifiers of the subsample are sorted without changing the original source sample. Most Statistics algorithms (that derive from StatisticsAlgorithmBase accept Subsample objects as inputs)
itk::Functor::SubtractConstantFrom< TInput, TConstant, TOutput >
itk::SubtractConstantFromImageFilter< TInputImage, TConstant, TOutputImage >Subract a constant from all input pixels
itk::SubtractImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements an operator for pixel-wise subtraction of two images
itk::Function::SumAccumulator< TInputPixel, TOuputPixel >
itk::Statistics::SumInputFunction< TMeasurementVector, ScalarType >
itk::Functor::SumLabelObjectAccessor< TLabelObject >
itk::Functor::SummerColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::SumOfSquaresImageFunction< TInputImage, TCoordRep >Calculate the sum of squares in the neighborhood of a pixel
itk::SumProjectionImageFilter< TInputImage, TOutputImage >Sum projection
itk::SurfaceSpatialObject< TDimension >Representation of a Surface based on the spatial object classes
itk::SurfaceSpatialObjectPoint< TPointDimension >Point used for a Surface definition
itk::SymmetricEigenAnalysis< TMatrix, TVector, TEigenMatrix >Find Eigen values of a real 2D symmetric matrix. It serves as a thread safe alternative to the class: vnl_symmetric_eigensystem, which uses netlib routines
itk::Functor::SymmetricEigenAnalysisFunction< TInput, TOutput >
itk::SymmetricEigenAnalysisImageFilter< TInputImage, TOutputImage >Computes the eigen-values of every input symmetric matrix pixel
itk::SymmetricEigenSystem< TMatrixElement, VNumberOfRows >Wrapper of the vnl_symmetric_eigensystem algorithm
itk::SymmetricEllipsoidInteriorExteriorSpatialFunction< VDimension, TInput >
itk::SymmetricForcesDemonsRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >Deformably register two images using the demons algorithm
itk::SymmetricForcesDemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >
itk::SymmetricSecondRankTensor< TComponent, NDimension >Represent a symmetric tensor of second rank
itk::Statistics::SymmetricSigmoidTransferFunction< ScalarType >
itk::SysResourceMemoryUsageObserver
itk::Function::Tan< TInput, TOutput >
itk::Statistics::TanHTransferFunction< ScalarType >
itk::TanImageAdaptor< TImage, TOutputPixelType >Presents an image as being composed of the vcl_tan() of its pixels
itk::TanImageFilter< TInputImage, TOutputImage >Computes the vcl_tan(x) pixel-wise
itk::Accessor::TanPixelAccessor< TInternalType, TExternalType >Give access to the vcl_tan() function of a value
itk::Statistics::TanSigmoidTransferFunction< ScalarType >
itk::TargetClass
itk::Statistics::TDistributionTDistribution class defines the interface for a univariate Student-t distribution (pdfs, cdfs, etc.)
itk::Functor::TensorFractionalAnisotropyFunction< TInput >
itk::TensorFractionalAnisotropyImageFilter< TInputImage, TOutputImage >Computes the Fractional Anisotropy for every pixel of a input tensor image
itk::Functor::TensorRelativeAnisotropyFunction< TInput >
itk::TensorRelativeAnisotropyImageFilter< TInputImage, TOutputImage >Computes the Relative Anisotropy for every pixel of a input tensor image
itk::TernaryAddImageFilter< TInputImage1, TInputImage2, TInputImage3, TOutputImage >Implements pixel-wise addition of three images
itk::TernaryFunctorImageFilter< TInputImage1, TInputImage2, TInputImage3, TOutputImage, TFunction >Implements pixel-wise generic operation of three images
itk::TernaryMagnitudeImageFilter< TInputImage1, TInputImage2, TInputImage3, TOutputImage >Implements pixel-wise addition of three images
itk::TernaryMagnitudeSquaredImageFilter< TInputImage1, TInputImage2, TInputImage3, TOutputImage >Implements pixel-wise addition of three images
itk::TetrahedronCell< TCellInterface >
itk::TetrahedronCellTopology
itk::TextOutput
itk::ThinPlateR2LogRSplineKernelTransform< TScalarType, NDimensions >
itk::ThinPlateSplineKernelTransform< TScalarType, NDimensions >
itk::ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::ThreadData
itk::MultiThreader::ThreadInfoStruct
itk::ThreadLoggerClass ThreadLogger is meant for providing logging service as a separate thread
itk::NarrowBandImageFilterBase< TInputImage, TOutputImage >::ThreadRegionType
itk::ImageSource< TOutputImage >::ThreadStruct
itk::MatchCardinalityImageToImageMetric< TFixedImage, TMovingImage >::ThreadStruct
itk::ThresholdImageFilter< TImage >Set image values to a user-specified value if they are below, above, or between simple threshold values
itk::Functor::ThresholdLabeler< TInput, TOutput >
itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >Label an input image according to a set of thresholds
itk::ThresholdMaximumConnectedComponentsImageFilter< TInputImage, TOutputImage >Finds the threshold value of an image based on maximizing the number of objects in the image that are larger than a given minimal size
itk::ThresholdSegmentationLevelSetFunction< TImageType, TFeatureImageType >This function is used in ThresholdSegmentationLevelSetImageFilter to segment structures in images based on intensity values
itk::ThresholdSegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in images based on intensity values
itk::TIFFImageIOImageIO object for reading and writing TIFF images
itk::TIFFImageIOFactoryCreate instances of TIFFImageIO objects using an object factory
itk::TileImageFilter< TInputImage, TOutputImage >Tile multiple input images into a single output image
itk::TileImageFilter< TInputImage, TOutputImage >::TileInfo
itk::TimeProbeClass for computing the time passed between two points in the code
itk::TimeProbesCollectorBaseClass for aggregating a set of time probes
itk::TimeStampGenerate a unique, increasing time value
itk::TobogganImageFilter< TInputImage >Toboggan image segmentation The Toboggan segmentation takes a gradient magnitude image as input and produces an (over-)segmentation of the image based on connecting each pixel to a local minimum of gradient. It is roughly equivalent to a watershed segmentation of the lowest level
itk::TorusInteriorExteriorSpatialFunction< VDimension, TInput >Spatial function implementation of torus symmetric about the z-axis in 3D
itk::Statistics::TrainingFunctionBase< TSample, TTargetVector, ScalarType >
itk::Statistics::TransferFunctionBase< ScalarType >
itk::Transform< TScalarType, NInputDimensions, NOutputDimensions >Transform points and vector from an input space to an output space
itk::TransformBase
itk::TransformFactory< T >Create instances of Transforms
itk::TransformFactoryBaseCreate instances of Transforms
itk::TransformFileReaderTODO
itk::TransformFileWriterTODO
itk::TransformIOBaseAbstract superclass defining the Transform IO interface
itk::TransformIOFactoryCreate instances of TransformIO objects using an object factory
itk::TransformMeshFilter< TInputMesh, TOutputMesh, TTransform >TransformMeshFilter applies a transform to all the points of a mesh
itk::TransformToDeformationFieldSource< TOutputImage, TTransformPrecisionType >Generate a deformation field from a coordinate transform
itk::TranslationTransform< TScalarType, NDimensions >Translation transformation of a vector space (e.g. space coordinates)
itk::TreeAddEvent< TTreeType >This class derives from TreeChangeEvent and check if a node has been added to the tree
itk::TreeChangeEvent< TTreeType >This class derives from ModifiedEvent and check if the position of a node in the tree has been changed
itk::TreeContainer< TValueType >TreeContainer class
itk::TreeContainerBase< TValueType >
itk::TreeIteratorBase< TTreeType >TreeIteratorBase class
itk::TreeIteratorClone< TObjectType >
itk::TreeNode< TValueType >TreeNode class
itk::TreeNodeChangeEvent< TTreeType >
itk::TreePruneEvent< TTreeType >
itk::TreeRemoveEvent< TTreeType >This class derives from TreeChangeEvent and check if a node has been removed from the tree
itk::TriangleCell< TCellInterface >
itk::TriangleCellTopology
itk::TriangleHelper< TPoint >Convenient class for various triangles elements computation in 2D or 3D
itk::TriangleMeshToBinaryImageFilter< TInputMesh, TOutputImage >3D Rasterization algorithm Courtesy of Dr David Gobbi of Atamai Inc
itk::TriangleMeshToSimplexMeshFilter< TInputMesh, TOutputMesh >This filter converts a triangle mesh into a 2-simplex mesh
itk::TubeSpatialObject< TDimension, TTubePointType >Representation of a tube based on the spatial object classes
itk::TubeSpatialObjectPoint< TPointDimension >Point used for a tube definition
itk::Statistics::TwoHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector >
itk::TwoOutputExampleImageFilter< TImage >Example of a filter that produce two outputs
itk::TxtTransformIO
itk::TxtTransformIOFactoryCreate instances of TxtTransformIO objects using an object factory
itk::UnaryCorrespondenceMatrix< TItemType >A matrix used to store the Unary Metric for medial node comparisons between two images
itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, TFunction >Implements pixel-wise generic operation on one image
itk::UnaryMedialNodeMetric< VDimensions >Compares the scale and dimensionality of two medial nodes
itk::UnconstrainedRegionBasedLevelSetFunctionSharedData< TInputImage, TFeatureImage, TSingleData >Helper class used to share data in the ScalarChanAndVeseLevelSetFunction
itk::Concept::Detail::UniqueType< T >
itk::Concept::Detail::UniqueType_bool< bool >
itk::Concept::Detail::UniqueType_int< int >
itk::Concept::Detail::UniqueType_unsigned_int< int >
itk::ImageIOBase::UnknownType
itk::UnsharpMaskLevelSetImageFilter< TInputImage, TOutputImage >This class implements a detail enhancing filter by making use of the 4th-order level set isotropic diffusion (smoothing) PDE
itk::ImageToImageFilterDetail::UnsignedIntDispatch< int >Templated class to produce a unique type for each unsigned integer (usually a dimension)
itk::UserEvent
itk::ValarrayImageContainer< TElementIdentifier, TElement >
itk::ValuedRegionalExtremaImageFilter< TInputImage, TOutputImage, TFunction1, TFunction2 >Uses a flooding algorithm to set all voxels that are not a regional extrema to the max or min of the pixel type
itk::ValuedRegionalMaximaImageFilter< TInputImage, TOutputImage >Transforms the image so that any pixel that is not a regional maxima is set to the minimum value for the pixel type. Pixels that are regional maxima retain their value
itk::ValuedRegionalMinimaImageFilter< TInputImage, TOutputImage >Transforms the image so that any pixel that is not a regional minima is set to the maximum value for the pixel type. Pixels that are regional minima retain their value
itk::VanHerkGilWermanDilateImageFilter< TImage, TKernel >
itk::VanHerkGilWermanErodeDilateImageFilter< TImage, TKernel, TFunction1 >Class to implement erosions and dilations using anchor methods. This is the base class that must be instantiated with appropriate definitions of greater, less and so on. The SetBoundary facility isn't necessary for operation of the anchor method but is included for compatability with other morphology classes in itk
itk::VanHerkGilWermanErodeImageFilter< TImage, TKernel >
VanHerkGilWermanUtilitiesFunctionality in common for anchor openings/closings and erosions/dilation
itk::Statistics::VariableDimensionHistogram< TMeasurement, TFrequencyContainer >This class is similar to the Histogram class. It however allows you to specify the histogram dimension at run time. (and is therefore not templated over the size of a measurement vector). Users who know that the length of a measurement vector will be fixed, for instance joint statistics on pixel values of 2 images, (where the dimension will be 2), etc should use the Histogram class instead
itk::VariableLengthVector< TValueType >VariableLengthVector is intended to represent an array whose length can be defined at run-time
itk::VariableSizeMatrix< T >A templated class holding a M x N size Matrix This class contains a vnl_matrix in order to make all the vnl mathematical methods available. This class is meant to be used when the matrix length cannot be determined at compile time
itk::VarianceImageFunction< TInputImage, TCoordRep >Calculate the variance in the neighborhood of a pixel
itk::Functor::VarianceLabelObjectAccessor< TLabelObject >
vcl_simple_alloc< T, Alloc >
vector
itk::Vector< T, NVectorDimension >A templated class holding a n-Dimensional vector
itk::VectorAnisotropicDiffusionFunction< TImage >
itk::Functor::VectorCast< TInput, TOutput >
itk::VectorCastImageFilter< TInputImage, TOutputImage >Casts input vector pixels to output vector pixel type
itk::VectorCentralDifferenceImageFunction< TInputImage, TCoordRep >Calculate the derivative by central differencing
itk::VectorConfidenceConnectedImageFilter< TInputImage, TOutputImage >Segment pixels with similar statistics using connectivity
itk::VectorConnectedComponentImageFilter< TInputImage, TOutputImage, TMaskImage >A connected components filter that labels the objects in a vector image. Two vectors are pointing similar directions if one minus their dot product is less than a threshold. Vectors that are 180 degrees out of phase are similar. Assumes that vectors are normalized
itk::VectorContainer< TElementIdentifier, TElement >
itk::VectorCurvatureAnisotropicDiffusionImageFilter< TInputImage, TOutputImage >
itk::VectorCurvatureNDAnisotropicDiffusionFunction< TImage >
itk::VectorExpandImageFilter< TInputImage, TOutputImage >Expand the size of a vector image by an integer factor in each dimension
itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >
itk::VectorGradientAnisotropicDiffusionImageFilter< TInputImage, TOutputImage >
itk::VectorGradientMagnitudeImageFilter< TInputImage, TRealType, TOutputImage >Computes a scalar, gradient magnitude image from a multiple channel (pixels are vectors) input
itk::VectorGradientNDAnisotropicDiffusionFunction< TImage >
itk::VectorImage< TPixel, VImageDimension >Templated n-dimensional vector image class
itk::VectorImageNeighborhoodAccessorFunctor< TImage >Provides accessor interfaces to Access pixels and is meant to be used on pointers to pixels held by the Neighborhood class
itk::VectorImageToImageAdaptor< TPixelType, Dimension >Presents a VectorImage and extracts a component from it into an image
itk::Accessor::VectorImageToImagePixelAccessor< TType >Extract components from a VectorImage
itk::Functor::VectorIndexSelectionCast< TInput, TOutput >
itk::VectorIndexSelectionCastImageFilter< TInputImage, TOutputImage >Extracts the selected index of the vector that is the input pixel type
itk::VectorInterpolateImageFunction< TInputImage, TCoordRep >Base class for all vector image interpolaters
itk::VectorLinearInterpolateImageFunction< TInputImage, TCoordRep >Linearly interpolate a vector image at specified positions
itk::VectorLinearInterpolateNearestNeighborExtrapolateImageFunction< TInputImage, TCoordRep >Linearly interpolate or NN extrapolate a vector image at specified positions
itk::Functor::VectorMagnitudeLinearTransform< TInput, TOutput >
itk::VectorMeanImageFunction< TInputImage, TCoordRep >Calculate the mean value in the neighborhood of a pixel in a Vector image
itk::VectorNearestNeighborInterpolateImageFunction< TInputImage, TCoordRep >Nearest neighbor interpolate a vector image at specified positions
itk::VectorNeighborhoodInnerProduct< TImage >
itk::VectorNeighborhoodOperatorImageFilter< TInputImage, TOutputImage >Applies a single scalar NeighborhoodOperator to an itk::Vector image region
itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >Resample an image via a coordinate transform
itk::VectorRescaleIntensityImageFilter< TInputImage, TOutputImage >Applies a linear transformation to the magnitude of pixel vectors in a vector Image
itk::VectorThresholdSegmentationLevelSetFunction< TImageType, TFeatureImageType >This function is used in VectorThresholdSegmentationLevelSetImageFilter to segment structures in images based on the Mahalanobis distance
itk::VectorThresholdSegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >Segments structures in images based on intensity values
itk::VectorToRGBImageAdaptor< TImage >Presents an image of pixel type Vector as being and image of RGBPixel type
itk::Accessor::VectorToRGBPixelAccessor< T >Give access to a Vector pixel type as if it were a RGBPixel type
itk::VersionTrack the current version of the software
itk::Versor< T >A templated class holding a unit quaternion
itk::VersorRigid3DTransform< TScalarType >VersorRigid3DTransform of a vector space (e.g. space coordinates)
itk::VersorRigid3DTransformOptimizerImplement a gradient descent optimizer for the VersorRigid3DTransform parameter space
itk::VersorTransform< TScalarType >
itk::VersorTransformOptimizerImplement a gradient descent optimizer
itk::VertexCell< TCellInterface >
itk::VesselTubeSpatialObject< TDimension >Representation of a tube based on the spatial object classes
itk::VesselTubeSpatialObjectPoint< TPointDimension >Point used for a tube definition
itk::fem::VisitorDispatcher< TVisitedClass, TVisitorBase, TVisitFunctionPointerType >This class provides the functionality needed to apply the correct visitor function to object of some class. The specific visitor function is choosen, based on a given pointer to some object
itk::fem::VisitorDispatcherTemplateHelper< TVisitedClass, TVisitorBase >
itk::VMMapData_10_2
itk::VMMapFileParser< TVMMapDataType >Read the output of a vmmap command and extract the memory usage information. Used for MAC OS X machines
itk::VMMapRecord
itk::VMMapSummaryRecord
vnl_fft_3d< T >
vnl_matrix
vnl_vector
itk::VnlFFTComplexConjugateToRealImageFilter< TPixel, VDimension >TODO
itk::VnlFFTRealToComplexConjugateImageFilter< TPixel, VDimension >TODO
VNLIterativeSparseSolverTraits< T >
VNLSparseLUSolverTraits
itk::VolumeSplineKernelTransform< TScalarType, NDimensions >
itk::VoronoiDiagram2D< TCoordType >Implements the 2-Dimensional Voronoi Diagram
itk::VoronoiDiagram2DGenerator< TCoordType >Implement the Sweep Line Algorithm for the construction of the 2D Voronoi Diagram
itk::VoronoiDiagram2D< TCoordType >::VoronoiEdge
itk::VoronoiPartitioningImageFilter< TInputImage, TOutputImage >
itk::VoronoiSegmentationImageFilter< TInputImage, TOutputImage, TBinaryPriorImage >
itk::VoronoiSegmentationImageFilterBase< TInputImage, TOutputImage, TBinaryPriorImage >Base class for VoronoiSegmentationImageFilter
itk::VoronoiSegmentationRGBImageFilter< TInputImage, TOutputImage >
itk::VotingBinaryHoleFillingImageFilter< TInputImage, TOutputImage >Fills in holes and cavities by applying a voting operation on each pixel
itk::VotingBinaryImageFilter< TInputImage, TOutputImage >Applies a voting operation in a neighborhood of each pixel
itk::VotingBinaryIterativeHoleFillingImageFilter< TImage >Fills in holes and cavities by iteratively applying a voting operation
itk::VoxBoCUBImageIORead VoxBoCUBImage file format
itk::VoxBoCUBImageIOFactoryCreate instances of VoxBoCUBImageIO objects using an object factory
itk::VTKImageExport< TInputImage >Connect the end of an ITK image pipeline to a VTK pipeline
itk::VTKImageExportBaseSuperclass for VTKImageExport instantiations
itk::VTKImageImport< TOutputImage >Connect the end of an VTK pipeline to an ITK image pipeline
itk::VTKImageIOImageIO class for reading VTK images
itk::VTKImageIO2ImageIO class for reading VTK images
itk::VTKImageIO2FactoryCreate instances of VTKImageIO2 objects using an object factory
itk::VTKImageIOFactoryCreate instances of VTKImageIO objects using an object factory
itk::VTKPolyDataReader< TOutputMesh >Reads a vtkPolyData file and create an itkMesh
itk::VTKPolyDataWriter< TInputMesh >Writes an itkMesh to a file in VTK file format
itk::WarpHarmonicEnergyCalculator< TInputImage >Compute the harmonic energy of a deformation field
itk::WarpImageFilter< TInputImage, TOutputImage, TDeformationField >Warps an image using an input deformation field
itk::WarpMeshFilter< TInputMesh, TOutputMesh, TDeformationField >WarpMeshFilter applies a deformation field to all the points of a mesh. The deformation field is represented as an image of Vectors
itk::WarpVectorImageFilter< TInputImage, TOutputImage, TDeformationField >Warps an image using an input deformation field
itk::WatershedImageFilter< TInputImage >A low-level image analysis algorithm that automatically produces a hierarchy of segmented, labeled images from a scalar-valued image input
itk::WatershedMiniPipelineProgressCommand
itk::WeakPointer< TObjectType >Implements a weak reference to an object
itk::Functor::WeightedAdd2< TInput1, TInput2, TOutput >
itk::WeightedAddImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements an operator for computing a weighted sum of two images pixel-wise
itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >This class generates a KdTree object with centroid information
itk::Statistics::WeightedCovarianceCalculator< TSample >Calculates the covariance matrix of the target sample data where each measurement vector has an associated weight value
itk::Statistics::WeightedCovarianceSampleFilter< TSample >Calculates the covariance matrix of the target sample data. where each measurement vector has an associated weight value
itk::Statistics::WeightedMeanCalculator< TSample >Calculates sample mean where each measurement vector has associated weight value
itk::Statistics::WeightedMeanSampleFilter< TSample >Given a sample where each measurement vector has associated weight value, this filter computes the sample mean
itk::Statistics::WeightSetBase< TMeasurementVector, TTargetVector >
itk::Function::WelchWindowFunction< VRadius, TInput, TOutput >Window function for sinc interpolation.

\[ w(x) = 1 - ( \frac{x^2}{m^2} ) \]

itk::WhiteTopHatImageFilter< TInputImage, TOutputImage, TKernel >White top hat extract local maxima that are larger than the structuring element
itk::Win32OutputWindowCollect error and debug messages on Win32-based systems
itk::WindowedSincInterpolateImageFunction< TInputImage, VRadius, TWindowFunction, TBoundaryCondition, TCoordRep >Use the windowed sinc function to interpolate
itk::Functor::WinterColormapFunctor< TScalar, TRGBPixel >Function object which maps a scalar value into an RGB colormap value
itk::WrapPadImageFilter< TInputImage, TOutputImage >Increase the image size by padding with replicants of the input image value
itk::XMLFileOutputWindowMessages sent from the system are sent to a file with each message enclosed by XML tags
itk::XMLFilterWatcherSimple mechanism for monitoring the pipeline events of a filter and reporting these events to std::cout. Formats reports with xml
itk::XMLReader< T >
itk::XMLReaderBase
itk::XMLWriterBase< T >
itk::Functor::XOR< TInput1, TInput2, TOutput >
itk::XorImageFilter< TInputImage1, TInputImage2, TOutputImage >Implements the XOR logical operator pixel-wise between two images
itk::ZeroCrossingBasedEdgeDetectionImageFilter< TInputImage, TOutputImage >
itk::ZeroCrossingImageFilter< TInputImage, TOutputImage >
itk::ZeroFluxNeumannBoundaryCondition< TImage >A function object that determines a neighborhood of values at an image boundary according to a Neumann boundary condition where first, upwind derivatives on the boundary are zero. This is a useful condition in solving some classes of differential equations

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