| 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 > | |
| itk::Functor::Add1< TInput, TOutput > | |
| itk::Functor::Add2< TInput1, TInput2, TOutput > | |
| itk::Function::Add3< TInput1, TInput2, TInput3, TOutput > | |
| itk::AddImageAdaptor< TImage > | Presents an image as being composed of the vcl_log() of its pixels |
| itk::AddImageFilter< TInputImage1, TInputImage2, TOutputImage > | Implements an operator for pixel-wise addition of two images |
| itk::Concept::AdditiveOperators< T1, T2, T3 > | |
| itk::Concept::AdditiveOperators< T1, T2, T3 >::Constraints | |
| 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::AmoebaOptimizer | Wrap of the vnl_amoeba algorithm |
| itk::AnalyzeImageIO | Class 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::AnalyzeImageIOFactory | Create instances of AnalyzeImageIO objects using an object factory |
| 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::ArchetypeSeriesFileNames | Generate an ordered sequence of filenames |
| 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::Concept::Assignable< T >::Constraints | |
| 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::AutomaticTopologyMeshSource< TOutputMesh > | Convenience class for generating meshes |
| itk::AutomaticTopologyMeshSource< TOutputMesh >::IdentifierArrayEqualsFunction | |
| itk::AutomaticTopologyMeshSource< TOutputMesh >::IdentifierArrayHashFunction | |
| 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::AuxVarTypeDefault< TPixel, VAuxDimension, VSetDimension > | Level set auxiliary variables type information.AuxVarTypeDefault is a simple class that holds type information for auxiliary variables in some level set algorithms. This class is templated over the auxiliary variable data type, the number of auxiliary variables and the level set dimension |
| 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 deformable model. For 3D (multi-slices) segmentation please use BalloonForce3DFilter The balloon force is vertical to the surface of the model. The potential force is given out by the estimated boundary points. These two will meet a balance at the boundary, thus the deformable model will fit to the boundary. Users should use deformable model as input using SetInput and also provide the filter with a potential image which will provide the estimated bounday. The image should be a binary image with object and background labelled differently. These image can be given by GibbsPriorFilter or any other segmentation filters. When the nodes on the model stopped at the estimated boundary, using the GradientFit method to fit the model using the gradient information in the original image |
| itk::BandNode< TIndexType, TDataType > | |
| itk::Barrier | Standard barrier class implementation for synchronizing the execution of threads |
| itk::BarycentricCombination< TPointContainer, TWeightContainer > | |
| 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::BinaryCrossStructuringElement< TPixel, VDimension, TAllocator > | A Neighborhood that represents a cross structuring element with binary elements |
| itk::BinaryDilateImageFilter< TInputImage, TOutputImage, TKernel > | Fast binary dilation |
| itk::BinaryErodeImageFilter< TInputImage, TOutputImage, TKernel > | Fast binary erosion |
| itk::BinaryFunctorImageFilter< TInputImage1, TInputImage2, TOutputImage, TFunction > | Implements pixel-wise generic operation of two images |
| 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::BinaryProjectionImageFilter< TInputImage, TOutputImage > | Binary projection |
| itk::BinaryPruningImageFilter< TInputImage, TOutputImage > | This filter removes "spurs" of less than a certain length in the input image |
| 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::BioRadImageIO | ImageIO 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::BioRadImageIOFactory | Create instances of BioRadImageIO objects using an object factory |
| itk::Function::BlackmanWindowFunction< VRadius, TInput, TOutput > | Window function for sinc interpolation.
![\[ w(x) = 0.42 + 0.5 cos(\frac{\pi x}{m}) + 0.08 cos(\frac{2 \pi x}{m}) \]](form_193.png)
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| 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 > | |
| 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::BloxItem | An entry in the BloxPixel linked list |
| itk::BloxPixel< TItemType > | Holds a linked list of BloxItem's |
| itk::BluePixelAccessor< T > | Give access to the Blue component of a RGBPixel type |
| itk::BMPImageIO | Read BMPImage file format |
| itk::BMPImageIOFactory | Create instances of BMPImageIO objects using an object factory |
| itk::ImageToImageFilterDetail::BooleanDispatch<> | Templated class to produce a unique type "true" and "false" |
| itk::watershed::Boundary< TScalarType, TDimension > | |
| itk::watershed::Boundary< TScalarType, TDimension >::face_pixel_t | |
| itk::watershed::Boundary< TScalarType, TDimension >::flat_region_t | |
| 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::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::Concept::BracketOperator< T1, T2, T3 >::Constraints | |
| itk::Brains2HeaderFactory | Create instances of Brains2Header objects using an object factory |
| itk::Brains2IPLHeaderInfo | |
| itk::Brains2MaskHeaderInfo | |
| itk::Brains2MaskImageIO | Class that defines how to read Brains2Mask file format |
| itk::Brains2MaskImageIOFactory | Create instances of Brains2MaskImageIO 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 > | |
| itk::BSplineDeformableTransform< TScalarType, NDimensions, VSplineOrder > | Deformable transform using a BSpline representation |
| 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::BSplineUpsampleImageFilter< TInputImage, TOutputImage, ResamplerType > | |
| BSplineUpsampleImageFilterBase | 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::CacheableScalarFunction | Function cache implementation |
| itk::NeighborhoodAlgorithm::CalculateOutputWrapOffsetModifiers< TImage > | |
| 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::CellBase | Non-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::CellInterface< TPixelType, TCellTraits >::MultiVisitor | A 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::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::CellularAggregateBase | Base 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::CentralDifferenceImageFunction< TInputImage, TCoordRep > | Calculate the derivative by central differencing |
| itk::ChainCodePath< VDimension > | Represent a path as a sequence of connected image index offsets |
| itk::ChainCodePath2D | Represent 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::CheckerBoardImageFilter< TImage > | Combines two images in a checkerboard pattern |
| itk::ChildTreeIterator< TTreeType > | |
| itk::Statistics::ChiSquareDistribution | ChiSquareDistribution class defines the interface for a univariate Chi-Square distribution (pdfs, cdfs, etc.) |
| itk::ClassifierBase< TDataContainer > | Base class for classifier object |
| itk::ClosingByReconstructionImageFilter< TInputImage, TOutputImage, TKernel > | Closing by reconstruction of an image |
| itk::CollidingFrontsImageFilter< TInputImage, TOutputImage > | Selects a region of space where two independent fronts run towards each other |
| itk::ColorTable< TPixel > | |
| itk::Command | Superclass for callback/observer methods |
| itk::Concept::Comparable< T1, T2 > | |
| itk::Concept::Comparable< T1, T2 >::Constraints | |
| itk::CompareHistogramImageToImageMetric< TFixedImage, TMovingImage > | Compares Histograms between two images to be registered to a Training Histogram |
| itk::Statistics::CompletelyConnectedWeightSet< TMeasurementVector, TTargetVector > | |
| 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 > | |
| Compose2DCovariantVectorImageFilter | Implements pixel-wise composition of an 2D covariant vector pixel from two scalar images |
| itk::Function::Compose2DVector< TInput > | |
| itk::Compose2DVectorImageFilter< TInputImage, TOutputImage > | |
| Compose2DVectorImageFilter | Implements pixel-wise composition of an 2D vector pixel from two scalar images |
| itk::Function::Compose3DCovariantVector< TInput > | |
| itk::Compose3DCovariantVectorImageFilter< TInputImage, TOutputImage > | |
| Compose3DCovariantVectorImageFilter | Implements pixel-wise composition of an 3D covariant vector pixel from three scalar images |
| itk::Function::Compose3DVector< TInput > | |
| itk::Compose3DVectorImageFilter< TInputImage, TOutputImage > | |
| Compose3DVectorImageFilter | Implements pixel-wise composition of an 3D vector pixel from three scalar images |
| itk::Function::ComposeRGB< TInput > | |
| itk::ComposeRGBImageFilter< TInputImage, TOutputImage > | |
| ComposeRGBImageFilter | Implements pixel-wise composition of an RGB pixel from three scalar images |
| itk::CompositeValleyFunction | Multiple 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::ConditionVariable | A 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< TPixelType > | ConformalFlatteningMeshFilter applies a conformal mapping from 3D to 2D |
| itk::ConicShellInteriorExteriorSpatialFunction< VDimension, TInput > | Spatial function implementation of a conic shell |
| itk::ConjugateGradientOptimizer | Wrap 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::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::ConstNeighborhoodIterator< TImage, TBoundaryCondition > | Const version of NeighborhoodIterator, defining iteration of a local N-dimensional neighborhood of pixels across an itk::Image |
| 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::ConstShapedNeighborhoodIterator< TImage, TBoundaryCondition > | Const version of ShapedNeighborhoodIterator, defining iteration of a local N-dimensional neighborhood of pixels across an itk::Image |
| itk::ConstShapedNeighborhoodIterator< TImage, TBoundaryCondition >::ConstIterator | |
| 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::Concept::Convertible< T1, T2 > | |
| itk::Concept::Convertible< T1, T2 >::Constraints | |
| itk::ConvertPixelBuffer< InputPixelType, OutputPixelType, OutputConvertTraits > | Class to convert blocks of data from one type to another |
| itk::Concept::CopyConstructible< T > | |
| itk::Concept::CopyConstructible< T >::Constraints | |
| 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.
![\[ w(x) = cos(\frac{\pi x}{2 m} ) \]](form_189.png)
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| itk::Accessor::CosPixelAccessor< TInternalType, TExternalType > | Give access to the vcl_cos() function of a value |
| itk::CostFunction | Base class for cost functions intended to be used with Optimizers |
| itk::CovarianceImageFunction< TInputImage, TCoordRep > | Calculate the covariance matrix in the neighborhood of a pixel in a Vector image |
| itk::CovariantVector< T, NVectorDimension > | A templated class holding a n-Dimensional covariant vector |
| itk::CreateObjectFunction< T > | CreateObjectFunction is used to create callback functions that create ITK Objects for use with the itk::ObjectFactory |
| itk::CreateObjectFunctionBase | Define 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::CStyleCommand | Command subclass that calls a pointer to a C function |
| itk::CumulativeGaussianCostFunction | Cost function for the Cumulative Gaussian Optimizer |
| itk::CumulativeGaussianOptimizer | This 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::CylinderSpatialObject | This class describe a cylinder in 3D only |
| itk::DanielssonDistanceMapImageFilter< TInputImage, TOutputImage > | |
| itk::DataObject | Base class for all data objects in ITK |
| itk::DataObjectDecorator< T > | Decorates any subclass of itkObject with a DataObject API |
| itk::DataObjectError | Exception object for DataObject exceptions |
| itk::DecisionRuleBase | Base 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::Concept::DefaultConstructible< T >::Constraints | |
| 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 > | |
| 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) |
| DeformableMesh3D | The 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. Inputs are: (1) A deformable triangular model (Mesh). Import using the SetInput method. (2) A gradient map that make the model deform to fit to the estimated boundary. the gradient should be based on the 2nd derive of the original image. So the nodes on the model surface will stop at the edge features in the original image |
| 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 |
| 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::DemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct | |
| itk::DenseFiniteDifferenceImageFilter< TInputImage, TOutputImage > | |
| itk::Statistics::DenseFrequencyContainer | His 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::DicomImageIO | Read DicomImage file format |
| itk::DICOMImageIO2 | Read DICOMImage file format |
| itk::DICOMImageIO2Factory | Create instances of DICOMImageIO2 objects using an object factory |
| itk::DicomImageIOFactory | Create instances of DicomImageIO objects using an object factory |
| itk::DICOMSeriesFileNames | Generate an ordered sequence of filenames |
| 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::Directory | Portable directory/filename traversal |
| 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::ImageToImageFilterDetail::DispatchBase | Base class for a class used to dispatch to dimension specific implementations |
| itk::Statistics::DistanceMetric< TVector > | This class declares common interfaces for distance functions |
| itk::Statistics::DistanceToCentroidMembershipFunction< TVector > | DistanceToCentroidMembershipFunction class represents DistanceToCentroid Density Function |
| itk::Function::Div< TInput1, TInput2, TOutput > | |
| itk::DivideImageFilter< TInputImage1, TInputImage2, TOutputImage > | Implements an operator for pixel-wise division of two images |
| itk::Concept::DivisionOperators< T1, T2, T3 > | |
| itk::Concept::DivisionOperators< T1, T2, T3 >::Constraints | |
| 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::DynamicLoader | Portable loading of dynamic libraries or dll's |
| 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 > | |
| itk::fem::Element | Abstract base element class |
| itk::fem::Element1DStress< TBaseClass > | Class that is used to define linear elasticity problem in 1D space |
| itk::fem::Element2DC0LinearLine | 2-noded, linear, C0 continuous line element in 2D space |
| itk::fem::Element2DC0LinearLineStress | 2-noded finite element class in 2D space for linear elasticity problem |
| itk::fem::Element2DC0LinearQuadrilateral | 4-noded, linear, C0 continuous finite element in 2D space |
| itk::fem::Element2DC0LinearQuadrilateralMembrane | 4-noded finite element class in 2D space for linear elasticity problem |
| itk::fem::Element2DC0LinearQuadrilateralStrain | 4-noded finite element class in 2D space for linear elasticity problem |
| itk::fem::Element2DC0LinearQuadrilateralStress | 4-noded finite element class in 2D space for linear elasticity problem |
| itk::fem::Element2DC0LinearTriangular | 3-noded, linear, C0 continuous finite element in 2D space |
| itk::fem::Element2DC0LinearTriangularMembrane | 3-noded finite element class in 2D space for linear elasticity problem |
| itk::fem::Element2DC0LinearTriangularStrain | 3-noded finite element class in 2D space for linear elasticity problem |
| itk::fem::Element2DC0LinearTriangularStress | 3-noded finite element class in 2D space for linear elasticity problem |
| itk::fem::Element2DC0QuadraticTriangular | 3-noded, quadratic, C0 continuous finite element in 2D space |
| itk::fem::Element2DC0QuadraticTriangularStrain | 3-noded finite element class in 2D space for linear elasticity problem |
| itk::fem::Element2DC0QuadraticTriangularStress | 3-noded finite element class in 2D space for linear elasticity problem |
| itk::fem::Element2DC1Beam | 1D 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::Element3DC0LinearHexahedron | 8-noded, linear, C0 continuous finite element in 3D space |
| itk::fem::Element3DC0LinearHexahedronMembrane | 8-noded finite element class in 3D space for linear elasticity problem |
| itk::fem::Element3DC0LinearHexahedronStrain | 8-noded finite element class in 3D space for linear elasticity problem |
| itk::fem::Element3DC0LinearTetrahedron | 4-noded, linear, C0 continuous finite element in 3D space |
| itk::fem::Element3DC0LinearTetrahedronMembrane | 4-noded finite element class in 3D space for linear elasticity problem |
| itk::fem::Element3DC0LinearTetrahedronStrain | 4-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::Element::Node | Class that stores information required to define a node |
| itk::fem::ElementStd< VNumberOfNodes, VNumberOfSpatialDimensions, TBaseClass > | Implements standard node management in the element classes |
| itk::EllipseSpatialObject< TDimension > | |
| itk::EllipsoidInteriorExteriorSpatialFunction< VDimension, TInput > | |
| EllipsoidSpatialFunction | Function implementation of an ellipsoid |
| EllipsoidSpatialFunction | Function implementation of an ellipsoid |
| itk::EndEvent | |
| itk::EndPickEvent | |
| itk::Concept::EqualityComparable< T1, T2 > | |
| itk::Concept::EqualityComparable< T1, T2 >::Constraints | |
| itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension > | |
| itk::EquivalencyTable | Hash table to manage integral label equivalencies |
| itk::ErodeObjectMorphologyImageFilter< TInputImage, TOutputImage, TKernel > | Erosion of an object in an image |
| itk::Statistics::ErrorBackPropagationLearningFunctionBase< LayerType, TTargetVector > | |
| ErrorBackPropagationLearningFunctionBase | The 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 > | |
| ErrorBackPropagationLearningWithMomentum | The 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::Statistics::EuclideanDistance< 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::Euler2DTransform< TScalarType > | Euler2DTransform of a vector space (e.g. space coordinates) |
| itk::Euler3DTransform< TScalarType > | Euler3DTransform of a vector space (e.g. space coordinates) |
| EulerOperatorCreateCenterVertexFunction | Create a vertex at the barycenter of the given face |
| EulerOperatorDeleteCenterVertexFunction | Delete the vertex, connected edges and faces and create a new face In place of the previous vertex' one-ring |
| EulerOperatorFlipEdgeFunction | Flip an edge |
| EulerOperatorJoinFacetFunction | Join the two facets which are on both sides of a given internal edge |
| EulerOperatorJoinVertexFunction | Collapse a given edge by joining its dest and its org |
| EulerOperatorSplitEdgeFunction | Given Edge is splitted into two and associated faces see their degree increased by one (a triangle is transformed into a quad for example) |
| EulerOperatorSplitFacetFunction | Given 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() |
| EulerOperatorSplitVertexFunction | For 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::EventObject | Abstraction of the Events used to communicating among filters and with GUIs |
| itk::ExhaustiveOptimizer | Optimizer 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::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< D1, D2 > | |
| 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::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::FastMarchingImageFilter< TLevelSet, TSpeedImage >::AxisNodeType | |
| itk::FastMarchingUpwindGradientImageFilter< TLevelSet, TSpeedImage > | Generates the upwind gradient field of fast marching arrival times |
| itk::FastMutexLock | Critical section locking class |
| itk::FastSymmetricForcesDemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField > | |
| itk::FastSymmetricForcesDemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct | |
| itk::fem::FEMException | Base class for all exception's that can occur within FEM classes |
| itk::fem::FEMExceptionIO | Base class for all IO exception's that can occur within FEM classe |
| itk::fem::FEMExceptionItpackSolver | Handles errors that occur in itpack solving routines |
| itk::fem::FEMExceptionItpackSparseMatrixSbagn | Handles errors that occur when unfinalizing the matrix |
| itk::fem::FEMExceptionItpackSparseMatrixSbsij | Handles errors that occur when building the matrix |
| itk::fem::FEMExceptionLinearSystem | |
| itk::fem::FEMExceptionLinearSystemBounds | |
| itk::fem::FEMExceptionObjectNotFound | Object not found exception |
| itk::fem::FEMExceptionSolution | Base class for all exceptions that can occur when solving FEM problem |
| itk::fem::FEMExceptionWrongClass | Bad object exception |
| itk::fem::FEMInitialization | FEM Library initialization and housekeeping |
| itk::fem::FEMLightObject | Base 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::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 |
| itk::fem::FEMRegistrationFilter< TMovingImage, TFixedImage >::FEMOF | |
| itk::FFTComplexConjugateToRealImageFilter< TPixel, Dimension > | |
| itk::FFTRealToComplexConjugateImageFilter< TPixel, Dimension > | |
| itk::FFTWComplexConjugateToRealImageFilter< TPixel, Dimension > | |
| itk::FFTWRealToComplexConjugateImageFilter< TPixel, Dimension > | |
| itk::FileOutputWindow | Messages 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::FiniteDifferenceSparseImageFilter< TInputImageType, TSparseOutputImageType >::FDThreadStruct | |
| 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::FixedArray< TValueType, VLength >::ConstReverseIterator | A const reverse iterator through the array |
| itk::FixedArray< TValueType, VLength >::ReverseIterator | A reverse iterator through the array |
| itk::FixedCenterOfRotationAffineTransform< TScalarType, NDimensions > | Affine transformation with a specified center of rotation |
| itk::FlatStructuringElement< NDimension > | 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::FRPROptimizer | Implements 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::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::GaussianDerivativeSpatialFunction< TOutput, VImageDimension, TInput > | N-dimensional gaussian spatial function class |
| itk::Statistics::GaussianDistribution | GaussianDistribution 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::GaussianKernelFunction | Gaussian kernel used for density estimation and nonparameteric regression |
| 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::GaussIntegrate | Use the Gauss-Legendre formula to perform integration |
| itk::GDCMImageIO | ImageIO class for reading and writing DICOM V3.0 and ACR/NEMA (V1.0 & V2.0) images This class is only an adaptor to the gdcm library (currently gdcm 1.2.x is used): |
| itk::GDCMImageIOFactory | Create instances of GDCMImageIO objects using an object factory |
| itk::GDCMSeriesFileNames | Generate a sequence of filenames from a DICOM series |
| itk::GE4ImageIO | Class that defines how to read GE4 file format |
| itk::GE4ImageIOFactory | Create instances of GE4ImageIO objects using an object factory |
| itk::GE5ImageIO | Class that defines how to read GE5 file format |
| itk::GE5ImageIOFactory | Create instances of GE5ImageIO objects using an object factory |
| itk::GEAdwImageIO | Class that defines how to read GEAdw file format |
| itk::GEAdwImageIOFactory | Create instances of GEAdwImageIO objects using an object factory |
| GEImageHeader | |
| itk::bio::Gene | This class implement the abstraction of a biological gene |
| itk::bio::Gene::ControlDomainType | |
| itk::bio::GeneNetwork | This class implement the abstraction of a biological gene network |
| itk::bio::Genome | This 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::GiplImageIO | Read GiplImage file format |
| itk::GiplImageIOFactory | Create instances of GiplImageIO objects using an object factory |
| 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::GradientDescentOptimizer | Implement 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 > | 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::Concept::GreaterThanComparable< T1, T2 >::Constraints | |
| itk::GreenPixelAccessor< T > | Give access to the Green component of a RGBPixel type |
| itk::Statistics::GreyLevelCooccurrenceMatrixTextureCoefficientsCalculator< THistogram > | This class computes texture feature coefficients from a grey level co-occurrence matrix |
| itk::GroupSpatialObject< TDimension > | Representation of a group based on the spatial object classes |
| itk::Function::HammingWindowFunction< VRadius, TInput, TOutput > | Window function for sinc interpolation.
![\[ w(x) = 0.54 + 0.46 cos(\frac{\pi x}{m} ) \]](form_190.png)
|
| itk::Statistics::HardLimitTransferFunction< ScalarType > | |
| 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::HasJoinTraits< T1, T2 >::Constraints | |
| itk::Concept::HasNumericTraits< T > | |
| itk::Concept::HasNumericTraits< T >::Constraints | |
| itk::Concept::HasPixelTraits< T > | |
| itk::Concept::HasPixelTraits< T >::Constraints | |
| itk::Concept::HasValueType< T > | |
| itk::Concept::HasValueType< T >::Constraints | |
| itk::Concept::HasZero< T > | |
| itk::Concept::HasZero< T >::Constraints | |
| 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::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
![\[\lambda_3\]](form_99.png)
close to 0 and
![\[\lambda_2\]](form_100.png)
and
![\[\lambda_1\]](form_101.png)
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::HexahedronCell< TCellInterface > | |
| itk::HexahedronCellTopology | |
| itk::Statistics::Histogram< TMeasurement, VMeasurementVectorSize, TFrequencyContainer > | This class stores measurement vectors in the context of n-dimensional histogram |
| itk::Statistics::Histogram< TMeasurement, VMeasurementVectorSize, TFrequencyContainer >::ConstIterator | |
| itk::Statistics::Histogram< TMeasurement, VMeasurementVectorSize, TFrequencyContainer >::Iterator | |
| itk::HistogramAlgorithmBase< TInputHistogram > | Base class for algorithms operating on histograms |
| itk::Function::HistogramEntropyFunction< TInput > | |
| itk::HistogramImageToImageMetric< TFixedImage, TMovingImage > | Computes similarity between two objects to be registered |
| itk::Function::HistogramIntensityFunction< TInput > | |
| itk::Function::HistogramLogProbabilityFunction< TInput > | |
| itk::HistogramMatchingImageFilter< TInputImage, TOutputImage, THistogramMeasurement > | Normalize the grayscale values between two image by histogram matching |
| itk::Function::HistogramProbabilityFunction< TInput > | |
| itk::HistogramToEntropyImageFilter< THistogram > | 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 > | 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 > | 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 > | 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::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::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::Statistics::HypersphereKernelMeanShiftModeSeeker< TSample > | Evolves the mode using a hyperspherical kernel defined by a radius (which is set by SetRadius) method |
| 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::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::ImageFileReaderException | Base exception class for IO conflicts |
| itk::ImageFileWriter< TInputImage > | Writes image data to a single file |
| itk::ImageFileWriterException | Base 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::ImageIOBase | Abstract superclass defines image IO interface |
| itk::ImageIOBase::UnknownType | |
| itk::ImageIOFactory | Create instances of ImageIO objects using an object factory |
| itk::ImageIORegion | An 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::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::ImageSeriesWriterException | Base 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.A multi-dimensional image iterator that extends the ImageLinearConstIteratorWithIndex 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. The slice orientation of the iterator is defined by specifying its two spanning axes using the methods: |
| 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::ImageSource< TOutputImage >::ThreadStruct | |
| 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::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::ImageToListAdaptor< TImage, TMeasurementVector >::ConstIterator | |
| itk::Statistics::ImageToListAdaptor< TImage, TMeasurementVector >::Iterator | |
| itk::Statistics::ImageToListGenerator< 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::Concept::IncrementDecrementOperators< T >::Constraints | |
| itk::Indent | Control indentation during Print() invocation |
| itk::Index< VIndexDimension > | Represent a n-dimensional index in a n-dimensional image |
| itk::IndexedContainerInterface< TElementIdentifier, TElement > | |
| itk::IndexedContainerInterface< TElementIdentifier, TElement >::ConstIterator | |
| itk::IndexedContainerInterface< TElementIdentifier, TElement >::Iterator | |
| itk::Functor::IndexLexicographicCompare< VIndexDimension > | Order Index instances lexicographically |
| itk::fem::INITClass | Class 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::Statistics::InputFunctionBase< TMeasurementVector, TTargetVector > | |
| itk::ImageToImageFilterDetail::IntDispatch<> | 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 > | |
| Interface | Wrapper 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::InvalidRequestedRegionError | |
| itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage > | Computes the inverse of a deformation field |
| itk::Functor::InvertIntensityFunctor< InputPixelType > | |
| itk::InvertIntensityImageFilter< TInputImage, TOutputImage > | Invert intensity of an image |
| itk::Functor::InvertIntensityTransform< TInput, TOutput > | |
| itk::IOCommon | Centralized funtionality for IO classes |
| itk::IPLCommonImageIO | Class 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::IsFixedPoint< T >::Constraints | |
| itk::Concept::IsFloatingPoint< T > | |
| itk::Concept::IsFloatingPoint< T >::Constraints | |
| itk::Concept::IsInteger< T > | |
| itk::Concept::IsInteger< T >::Constraints | |
| itk::Concept::IsNonInteger< T > | |
| itk::Concept::IsNonInteger< T >::Constraints | |
| 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::IterationReporter | Implements iterations tracking for a filter |
| itk::IterativeInverseDeformationFieldImageFilter< TInputImage, TOutputImage > | Computes the inverse of a deformation field |
| itk::Statistics::IterativeSupervisedTrainingFunction< TSample, TTargetVector, ScalarType > | |
| itk_simple_alloc< T, Alloc > | |
| itkBSplineCenteredL2ResampleImageFilterBase | Uses the "Centered L2" B-Spline pyramid implementation of B-Spline Filters to up/down sample an image by a factor of 2 |
| itkBSplineDecompositionImageFilter | Calculates the B-Spline coefficients of an image. Spline order may be from 0 to 5 |
| itkSparseFieldLayer | |
| itk::fem::ItpackSparseMatrix | Compressed row sparse matrix representation that makes use of itpack to dynamically assemble the matrix |
| 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::JPEGImageIO | ImageIO object for reading and writing JPEG images |
| itk::JPEGImageIOFactory | Create instances of JPEGImageIO objects using an object factory |
| itk::KalmanLinearEstimator< T, VEstimatorDimension > | Implement a linear recursive estimator |
| 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::KdTree< TSample >::NearestNeighbors | Data structure for storing k-nearest neighbor search result (k number of Neighbors) |
| itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree > | Fast k-means algorithm implementation using k-d tree structure |
| itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector | |
| itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate | |
| 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::KernelFunction | Kernel used for density estimation and nonparameteric regression |
| 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::KLMSegmentationBorder | Base class for KLMSegmentationBorder object |
| itk::KLMSegmentationRegion | Base 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::LabelOverlay< TInputPixel, TLabel, TRGBPixel > | A functor class used internally by LabelOverlayImageFilter |
| itk::LabelOverlayImageFilter< TInputImage, TLabelImage, TOutputImage > | Apply a colormap to a label image and put it on top of the input image |
| 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::LabelStatisticsImageFilter< TInputImage, TLabelImage >::LabelStatistics | |
| 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.
![\[ w(x) = \textrm{sinc} ( \frac{x}{m} ) \]](form_192.png)
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 > | |
| 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::LBFGSBOptimizer | Limited memory Broyden Fletcher Goldfarb Shannon minimization with simple bounds |
| itk::LBFGSOptimizer | Wrap of the vnl_lbfgs algorithm |
| itk::LeafTreeIterator< TTreeType > | |
| itk::Statistics::LearningFunctionBase< LayerType, TTargetVector > | |
| LearningFunctionBase | The 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::Concept::LessThanComparable< T1, T2 > | |
| itk::Concept::LessThanComparable< T1, T2 >::Constraints | |
| 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::LevelSetFunction< TImageType >::GlobalDataStruct | |
| 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::LevelSetMotionRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct | |
| 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::LevenbergMarquardtOptimizer | Wrap of the vnl_levenberg_marquardt algorithm |
| itk::LightObject | Light weight base class for most itk classes |
| itk::LightProcessObject | LightProcessObject 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::LinearSystemWrapper | Defines all functions required by Solver class to allocate, assemble and solve a linear system of equation |
| itk::fem::LinearSystemWrapperDenseVNL | LinearSystemWrapper class that uses VNL numeric library functions to define a sparse linear system of equations |
| itk::fem::LinearSystemWrapperItpack | LinearSystemWrapper class that uses Itpack numeric library functions to define and solve a sparse linear system of equations |
| itk::fem::LinearSystemWrapperVNL | LinearSystemWrapper 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 |
| itk::ListNode< TValueType > | |
| itk::Statistics::ListSample< TMeasurementVector > | This class is the native implementation of the ListSampleBase |
| itk::Statistics::ListSample< TMeasurementVector >::ConstIterator | |
| itk::Statistics::ListSample< TMeasurementVector >::Iterator | |
| 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::Load | General abstract load base class |
| itk::fem::LoadBC | Generic essential (Dirichlet) boundary conditions |
| itk::fem::LoadBCMFC | Generic linear multi freedom displacement constraint in global coordinate system |
| itk::fem::LoadBCMFC::MFCTerm | Class that holds information about one term in MFC constraint equation |
| itk::fem::LoadEdge | A generic load that can be applied to an edge of the element |
| itk::fem::LoadElement | Virtual element load base class |
| itk::fem::LoadGrav | Abstract gravity load class |
| itk::fem::LoadGravConst | Constant gravity load class |
| itk::fem::LoadImplementationGenericBodyLoad | Class that holds a templated generic body load implementation |
| itk::fem::LoadImplementationGenericLandmarkLoad | Class that holds a templated generic landmark load implementation |
| itk::fem::LoadImplementationTest< TLoadClass > | Example implementation of templated LoadTest class |
| itk::fem::LoadLandmark | This load is derived from the motion of a specific landmark |
| itk::fem::LoadNode | This load is applied on a specific point within the system |
| itk::fem::LoadPoint | This 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::Logger | Class Logger is meant for logging information during a run |
| itk::LoggerBase | Class LoggerBase is meant for logging information during a run |
| itk::LoggerManager | Class LoggerManager is meant for centrally managing loggers |
| itk::LoggerOutput | This 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::Concept::LogicalOperators< T1, T2, T3 >::Constraints | |
| 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::LogOutput | Class 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::LSMImageIO | ImageIO 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::LSMImageIOFactory | Create instances of LSMImageIO objects using an object factory |
| itk::Statistics::MahalanobisDistanceMembershipFunction< TVector > | MahalanobisDistanceMembershipFunction class represents MahalanobisDistance Density Function |
| 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 > | |
| itk::MapContainer< TElementIdentifier, TElement > | |
| itk::MapContainer< TElementIdentifier, TElement >::ConstIterator | The const iterator type for the map |
| itk::MapContainer< TElementIdentifier, TElement >::Iterator | The non-const iterator type for the map |
| 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::MatchCardinalityImageToImageMetric< TFixedImage, TMovingImage >::ThreadStruct | |
| itk::fem::Material | Base class for storing all the implicit material and other properties required to fully define the element class |
| itk::fem::MaterialLinearElasticity | Linear elasticity material class |
| itk::MatlabTransformIO | |
| itk::MatlabTransformIOFactory | Create 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::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::Function::Maximum< TInput1, TInput2, TOutput > | |
| itk::Functor::Maximum1< TInput, TOutput > | |
| itk::Function::MaximumAccumulator< TInputPixel > | |
| itk::MaximumDecisionRule | A Decision rule that choose the class of which discriminant score is the largest |
| itk::MaximumImageFilter< TInputImage1, TInputImage2, TOutputImage > | Implements a pixel-wise operator Max(a,b) between two images |
| itk::MaximumProjectionImageFilter< TInputImage, TOutputImage > | Maximum projection |
| itk::MaximumRatioDecisionRule | This rule returns  if  for all  , where the is the index of a class which has membership function  and its prior value (usually, the a priori probability or the size of a class) is  |
| 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::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::MeanShiftModeCacheMethod< TMeasurementVector > | This class stores mappings between a query point and its resulting mode point |
| itk::Statistics::MeanShiftModeCacheMethod< TMeasurementVector >::LessMeasurementVector | |
| 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::MeanSquareRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct | |
| 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::MeasurementVectorTraits | |
| 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::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::MembershipSample< TSample >::ConstIterator | |
| itk::Statistics::MembershipSampleGenerator< TInputSample, TClassMaskSample > | MembershipSampleGenerator generates a MembershipSample object using a class mask sample |
| itk::Statistics::MersenneTwisterRandomVariateGenerator | MersenneTwisterRandom random variate generator |
| itk::Mesh< TPixelType, VDimension, TMeshTraits > | Implements the N-dimensional mesh structure |
| itk::Mesh< TPixelType, VDimension, TMeshTraits >::BoundaryAssignmentIdentifier | |
| MeshFunctionBase | Fuse the incoming edge and it's Onext() follower (like a zipper does) |
| MeshFunctionBase | Base class for mesh function object modifiers |
| itk::MeshRegion | A 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::MetaDataObjectBase | The MetaDataObjectBase class is designed 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::MetaEvent | |
| itk::MetaGaussianConverter< NDimensions > | |
| itk::MetaGroupConverter< NDimensions > | |
| itk::MetaImageConverter< NDimensions, PixelType > | |
| itk::MetaImageIO | Read MetaImage file format |
| itk::MetaImageIOFactory | Create 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::MINC2ImageIO | Class 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::MINC2ImageIOFactory | Create instances of MINC2ImageIO objects using an object factory |
| itk::Function::Minimum< TInput1, TInput2, TOutput > | |
| itk::Function::MinimumAccumulator< TInputPixel > | |
| itk::MinimumDecisionRule | A Decision rule that choose the class that has minimum value |
| itk::MinimumImageFilter< TInputImage1, TInputImage2, TOutputImage > | Implements a pixel-wise operator Min(a,b) between two images |
| itk::MinimumMaximumImageCalculator< TInputImage > | |
| itk::MinimumMaximumImageFilter< TInputImage > | Computes the minimum and the maximum intensity values of an image |
| itk::MinimumProjectionImageFilter< TInputImage, TOutputImage > | Minimum projection |
| itk::MinMaxCurvatureFlowFunction< TImage > | |
| itk::MinMaxCurvatureFlowImageFilter< TInputImage, TOutputImage > | Denoise an image using min/max curvature flow |
| itk::MIRegistrationFunction< TFixedImage, TMovingImage, TDeformationField > | |
| itk::MIRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct | |
| 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::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::MorphologyImageFilter< TInputImage, TOutputImage, TKernel > | Base class for the morphological operations such as erosion and dialation |
| itk::MRASlabIdentifier< TInputImage > | Identifies slab in MR images comparing minimum intensity averages |
| 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::MultipleLogOutput | Class MultipleLogOutput allows writing simultaneously to multiple streams. Note that the class derives from std::streambuf and contains a std::set<> of LogOutput |
| itk::MultipleValuedCostFunction | This class is a base for the CostFunctions returning a multiple values |
| itk::MultipleValuedNonLinearOptimizer | This class is a base for the Optimization methods that optimize a multiple valued function |
| itk::MultipleValuedNonLinearVnlOptimizer | This class is a base for the Optimization methods that optimize a multi-valued function |
| itk::MultipleValuedVnlCostFunctionAdaptor | This class is an Adaptor that allows to pass itk::MultipleValuedCostFunctions to vnl_optimizers expecting a vnl_cost_function |
| itk::Concept::MultiplyAndAssignOperator< T1, T2 > | |
| itk::Concept::MultiplyAndAssignOperator< T1, T2 >::Constraints | |
| itk::MultiplyImageFilter< TInputImage1, TInputImage2, TOutputImage > | Implements an operator for pixel-wise multiplication of two images |
| itk::Concept::MultiplyOperator< T1, T2, T3 > | |
| itk::Concept::MultiplyOperator< T1, T2, T3 >::Constraints | |
| itk::Statistics::MultiquadricRadialBasisFunction< ScalarType > | |
| itk::MultiResolutionImageRegistrationMethod< TFixedImage, TMovingImage > | Base class for multi-resolution image registration methods |
| itk::MultiResolutionPDEDeformableRegistration< TFixedImage, TMovingImage, TDeformationField > | Framework for perfoming multi-resolution PDE deformable registration |
| itk::MultiResolutionPyramidImageFilter< TInputImage, TOutputImage > | Framework for creating images in a multi-resolution pyramid |
| itk::MultiThreader | A class for performing multithreaded execution |
| itk::MultiThreader::ThreadInfoStruct | |
| itk::MultivariateLegendrePolynomial | 2D and 3D multivariate Legendre Polynomial |
| itk::MultivariateLegendrePolynomial::CoefficientVectorSizeMismatch | |
| itk::MultivariateLegendrePolynomial::SimpleForwardIterator | |
| itk::MutexLock | Mutual 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 |
| itk::MutualInformationImageToImageMetric< TFixedImage, TMovingImage > | Computes the mutual information between two images to be registered |
| itk::NarrowBand< NodeType > | |
| itk::NarrowBand< NodeType >::RegionStruct | |
| 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::NarrowBandImageFilterBase< TInputImage, TOutputImage >::ThreadRegionType | |
| 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 > | |
| 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::NCCRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct | |
| itk::NearestNeighborExtrapolateImageFunction< TInputImage, TCoordRep > | Nearest neighbor extrapolation of a scalar image |
| itk::NearestNeighborInterpolateImageFunction< TInputImage, TCoordRep > | Nearest neighbor interpolation of a scalar image |
| 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::NiftiImageIO | Class 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::NiftiImageIOFactory | Create instances of NiftiImageIO objects using an object factory |
| itk::Statistics::NNetDistanceMetricBase< TMeasurementVector > | |
| 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::NonLinearOptimizer | Wrap 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::NormalVariateGenerator | Normal 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 > | |
| itk::Functor::NOT< TInput, TOutput > | |
| itk::NotImageFilter< TInputImage, TOutputImage > | Implements the NOT logical operator pixel-wise on an image |
| itk::Concept::NotOperator< T > | |
| itk::Concept::NotOperator< T >::Constraints | |
| itk::NrrdImageIO | Read 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::NrrdImageIOFactory | Create 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::NumericSeriesFileNames | Generate an ordered sequence of filenames |
| NumericTraits | Define traits for type RGBPixel<unsigned short> |
| NumericTraits | Define traits for type RGBPixel<unsigned char> |
| itk::NumericTraits< RGBPixel< unsigned char > > | |
| itk::NumericTraits< RGBPixel< unsigned short > > | |
| itk::Object | Base class for most itk classes |
| itk::ObjectFactory< T > | Create instances of a class |
| itk::ObjectFactoryBase | Create instances of classes using an object factory |
| itk::ObjectFactoryBase::OverrideInformation | Internal implementation class for ObjectFactorBase |
| 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::ObjectStore< TObjectType >::MemoryBlock | |
| itk::Octree< TPixel, ColorTableSize, MappingFunctionType > | Represent a 3D Image with an Octree data structure |
| itk::OctreeBase | Provides 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::Statistics::OneHiddenLayerBackPropagationNeuralNetwork< TMeasurementVector, TTargetVector > | |
| itk::OnePlusOneEvolutionaryOptimizer | 1+1 evolutionary strategy optimizer |
| itk::OneWayEquivalencyTable | Hash table to manage integral label equivalencies that are order dependent |
| itk::OpeningByReconstructionImageFilter< TInputImage, TOutputImage, TKernel > | Opening by reconstruction of an image |
| itk::Optimizer | Generic 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::OrthogonallyCorrected2DParametricPath | Represent 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::Concept::OStreamWritable< T >::Constraints | |
| 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::OutputWindow | Messages sent from the system are collected by this object |
| itk::PadImageFilter< TInputImage, TOutputImage > | Increase the image size by padding. Superclass for filters that fill in extra pixels |
| 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::ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::ParallelSparseFieldLevelSetThreadStruct | |
| itk::ParallelSparseFieldLevelSetImageFilter< TInputImage, TOutputImage >::ThreadData | |
| itk::ParallelSparseFieldLevelSetNode< TNodeIndexType > | |
| 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::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::PickEvent | |
| itk::PixelAccessor< TInternalType, TExternalType > | Give access to partial aspects of a type |
| itk::PlaneSpatialObject< TDimension > | |
| itk::PNGImageIO | ImageIO object for reading and writing PNG images |
| itk::PNGImageIOFactory | Create 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::PointSetToListAdaptor< TPointSet >::ConstIterator | |
| itk::Statistics::PointSetToListAdaptor< TPointSet >::Iterator | |
| 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 > | |
| 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::PowellOptimizer | Implements Powell optimization using Brent line search |
| itk::PreOrderTreeIterator< TTreeType > | |
| itk::Statistics::ProbabilityDistribution | ProbabilityDistribution class defines common interface for statistical distributions (pdfs, cdfs, etc.) |
| itk::ProcessObject | ProcessObject is the base class for all process objects (source, filters, mappers) in the Insight data processing pipeline |
| itk::Statistics::ProductInputFunction< TMeasurementVector, ScalarType > | |
| itk::ProgressAccumulator | Facilitates progress reporting for filters that wrap around multiple other filters |
| itk::ProgressEvent | |
| itk::ProgressReporter | Implements progress tracking for a filter |
| itk::ProjectionImageFilter< TInputImage, TOutputImage, TAccumulator > | Implements an accumulation of an image along a selected direction |
| itk::fftw::Proxy< TPixel > | |
| itk::QuadEdge | Base 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::QuadEdgeMeshBoundaryEdgesMeshFunction< TMesh > | Build a list of references to edges (as GeometricalQuadEdge::RawPointer) each one representing a different boundary component |
| itk::QuadEdgeMeshCellTraitsInfo< VPointDimension, TCoordRep, TInterpolationWeight, TPointIdentifier, TCellIdentifier, TCellFeatureIdentifier, TPoint, TPointsContainer, TUsingCellsContainer, TQE > | Helper class holding the traits of QuadEdge cells |
| itk::QuadEdgeMeshConstFrontIterator< TMesh, TQE > | Const quad edge mesh front iterator |
| itk::QuadEdgeMeshConstIterator< TQuadEdge > | Const iterator for QuadEdgeMesh |
| itk::QuadEdgeMeshConstIteratorGeom< TGeometricalQuadEdge > | Const geometrical iterator |
| 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::QuadEdgeMeshFrontBaseIterator< TMesh, TQE > | Front iterator on Mesh class |
| itk::QuadEdgeMeshFrontBaseIterator< TMesh, TQE >::FrontAtom | Atomic information associated to each edge of the front |
| 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::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::QuadEdgeMeshTopologyChecker< TMesh > | Make some basic checks in order to assert 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< Dimension > | Converts QuaternionOrientation flags to/from direction cosines |
| itk::QuaternionRigidTransform< TScalarType > | QuaternionRigidTransform of a vector space (e.g. space coordinates) |
| itk::QuaternionRigidTransformGradientDescentOptimizer | Implement 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::RandomVariateGeneratorBase | This class defines common interfaces for random variate generators |
| 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::ReadInfoType | Helper class for storing additional information that is required when reading FEM objects from stream |
| itk::RealTimeClock | The 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::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::Region | A 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::RegionGrowImageFilter< TInputImage, TOutputImage > | Base class for RegionGrowImageFilter object |
| itk::RegionOfInterestImageFilter< TInputImage, TOutputImage > | Extract a region of interest from the input image |
| itk::RegularExpressionSeriesFileNames | Generate an ordered sequence of filenames that match a regular expression |
| 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::RegularStepGradientDescentBaseOptimizer | Implement a gradient descent optimizer |
| itk::RegularStepGradientDescentOptimizer | Implement 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::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::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 > | |
| itk::Rigid3DPerspectiveTransform< TScalarType > | Rigid3DTramsform of a vector space (e.g. space coordinates) |
| itk::Rigid3DTransform< TScalarType > | Rigid3DTransform of a vector space (e.g. space coordinates) |
| Rigig2DTransform | Rigid2DTransform of a vector space (e.g. space coordinates) |
| itk::RootTreeIterator< TTreeType > | |
| itk::Concept::SameDimension< D1, D2 > | |
| itk::Concept::SameDimension< D1, D2 >::Constraints | |
| itk::Concept::SameDimensionOrMinusOne< D1, D2 > | |
| itk::Concept::SameDimensionOrMinusOne< D1, D2 >::Constraints | |
| itk::Concept::SameType< T1, T2 > | |
| itk::Concept::SameType< T1, T2 >::Constraints | |
| 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::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::SampleToHistogramProjectionFilter< TInputSample, THistogramMeasurement > | Projects measurement vectors on to an axis to generate an 1D histogram |
| itk::ScalableAffineTransform< TScalarType, NDimensions > | Affine transformation with a specified center of rotation |
| itk::ScalarAnisotropicDiffusionFunction< TImage > | |
| 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 > | 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::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 > | |
| itk::Statistics::ScalarImageToListAdaptor< TImage > | This class provides ListSampleBase interfaces to ITK Image |
| 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::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::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::SegmentationBorder | Base 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::SegmentationRegion | Base class for SegmentationRegion object |
| itk::watershed::Segmenter< TInputImage > | |
| itk::watershed::Segmenter< TInputImage >::connectivity_t | |
| itk::watershed::Segmenter< TInputImage >::flat_region_t | |
| itk::watershed::SegmentTable< TScalarType > | |
| itk::watershed::SegmentTable< TScalarType >::edge_pair_t | |
| itk::watershed::SegmentTable< TScalarType >::segment_t | |
| itk::watershed::SegmentTree< TScalarType > | |
| itk::watershed::SegmentTree< TScalarType >::merge_comp | |
| itk::watershed::SegmentTree< TScalarType >::merge_t | |
| itk::watershed::SegmentTree< TScalarType >::sort_comp | |
| 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::Semaphore | The 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::ShapedNeighborhoodIterator< TImage, TBoundaryCondition > | A neighborhood iterator which can take on an arbitrary shape |
| itk::ShapedNeighborhoodIterator< TImage, TBoundaryCondition >::Iterator | |
| 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::ShapePriorSegmentationLevelSetFunction< TImageType, TFeatureImageType >::ShapePriorGlobalDataStruct | |
| itk::ShapePriorSegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType > | A base class which defines the API for implementing a level set segmentation filter with statistical shape influence |
| itk::ShapeSignedDistanceFunction< TCoordRep, VSpaceDimension > | Base class for functions which evaluates the signed distance from a shape |
| itk::ShiftScaleImageFilter< TInputImage, TOutputImage > | Shift and scale the pixels in an image |
| itk::ShiftScaleInPlaceImageFilter< TInputImage > | Shift and scale the pixels in an image |
| itk::ShrinkImageFilter< TInputImage, TOutputImage > | Reduce the size of an image by an integer factor in each dimension |
| itk::SiemensVisionImageIO | Class that defines how to read SiemensVision file format |
| itk::SiemensVisionImageIOFactory | Create instances of SiemensVisionImageIO objects using an object factory |
| itk::Function::Sigmoid< TInput, TOutput > | |
| itk::SigmoidImageFilter< TInputImage, TOutputImage > | Computes the sigmoid function pixel-wise |
| itk::Statistics::SigmoidTransferFunction< ScalarType > | |
| itk::Concept::Signed< T > | |
| itk::Concept::Signed< T >::Constraints | |
| itk::SignedDanielssonDistanceMapImageFilter< TInputImage, TOutputImage > | |
| itk::Statistics::SignedHardLimitTransferFunction< ScalarType > | |
| itk::SignedMaurerDistanceMapImageFilter< TInputImage, TOutputImage > | |
| SignedMaurerDistanceMapImageFilter | 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 > | |
| SimilarVectorsFunctor | 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::SimpleFastMutexLock | Critical section locking class that can be allocated on the stack |
| itk::SimpleFilterWatcher | Simple mechanism for monitoring the pipeline events of a filter and reporting these events to std::cout |
| 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::SimpleMutexLock | Simple mutual exclusion locking class |
| 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::SimplexMeshAdaptTopologyFilter< TInputMesh, TOutputMesh >::SimplexCellVisitor | |
| itk::SimplexMeshGeometry | Handle geometric properties for vertices of a simplx mesh |
| itk::SimplexMeshToTriangleMeshFilter< TInputMesh, TOutputMesh > | This filter converts a 2-simplex mesh into a triangle mesh |
| itk::SimplexMeshToTriangleMeshFilter< TInputMesh, TOutputMesh >::SimplexCellVisitor | |
| 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::SimplexMeshVolumeCalculator< TInputMesh >::SimplexCellVisitor | |
| itk::Function::Sin< TInput, TOutput > | |
| itk::SingleValuedCostFunction | This class is a base for the CostFunctions returning a single value |
| itk::SingleValuedNonLinearOptimizer | This class is a base for the Optimization methods that optimize a single valued function |
| itk::SingleValuedNonLinearVnlOptimizer | This class is a base for the Optimization methods that optimize a single valued function |
| itk::SingleValuedVnlCostFunctionAdaptor | This 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::Size< VDimension > | Represent the size (bounds) of a n-dimensional image |
| itk::SliceIterator< TPixel, TContainer > | A flexible iterator for itk containers(i.e. itk::Neighborhood) that support pixel access through operator[] |
| 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::fem::Solution | Provides functions to access the values of the solution vector |
| itk::fem::Solver | Main FEM solver |
| itk::fem::SolverHyperbolic | Solver class suitable for hyperbolic problems |
| 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::SparseFieldLayer< TNodeType >::RegionType | |
| 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::SparseFrequencyContainer | His 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::SpatialObjectFactoryBase | Create instances of SpatialObjects |
| itk::SpatialObjectPoint< TPointDimension > | Point used for spatial objets |
| itk::SpatialObjectProperty< TComponentType > | |
| itk::SpatialObjectReader< NDimensions, PixelType, TMeshTraits > | |
| 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 > | |
| itk::SpatialObjectWriter< NDimensions, PixelType, TMeshTraits > | |
| itk::SpatialOrientationAdapter | Converts 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::SPSAOptimizer | An 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::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 |
| list | |
| itk::StdStreamLogOutput | Class StdStreamLogOutput represents a standard stream output stream. This class provides thread safety for the standard stream output stream |
| itk::StimulateImageIO | ImageIO 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::StimulateImageIOFactory | Create instances of StimulateImageIO objects using an object factory |
| itk::STLConstContainerAdaptor< TContainer > | |
| itk::STLContainerAdaptor< TContainer > | |
| itk::StreamingImageFilter< TInputImage, TOutputImage > | Pipeline object to control data streaming for large data processing |
| 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::Statistics::Subsample< TSample >::ConstIterator | |
| itk::Statistics::Subsample< TSample >::Iterator | |
| 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::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 Fractional Anisotropy for every pixel of a input tensor image |
| 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::SymmetricForcesDemonsRegistrationFunction< TFixedImage, TMovingImage, TDeformationField >::GlobalDataStruct | |
| itk::SymmetricSecondRankTensor< TComponent, NDimension > | Represent a symmetric tensor of second rank |
| itk::Statistics::SymmetricSigmoidTransferFunction< ScalarType > | |
| 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::TDistribution | TDistribution 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::ThreadLogger | Class ThreadLogger is meant for providing logging service as a separate thread |
| 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::TIFFImageIO | ImageIO object for reading and writing TIFF images |
| itk::TIFFImageIOFactory | Create 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::TimeProbe | Class for computing the time passed between two points in the code |
| itk::TimeProbesCollectorBase | Class for aggregating a set of time probes |
| itk::TimeStamp | Generate 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::TransformFactoryBase | Create instances of Transforms |
| itk::TransformFileReader | |
| itk::TransformFileWriter | |
| itk::TransformIOBase | Abstract superclass defining the Transform IO interface |
| itk::TransformIOFactory | Create 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::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::TreeRemoveEvent< TTreeType > | This class derives from TreeChangeEvent and check if a node has been removed from the tree |
| itk::TriangleCell< TCellInterface > | |
| itk::TriangleCellTopology | |
| 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::TxtTransformIOFactory | Create 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::Concept::Detail::UniqueType< T > | |
| itk::Concept::Detail::UniqueType_bool<> | |
| itk::Concept::Detail::UniqueType_int<> | |
| itk::Concept::Detail::UniqueType_unsigned_int< int > | |
| 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::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::Statistics::VariableDimensionHistogram< TMeasurement, TFrequencyContainer >::ConstIterator | |
| itk::Statistics::VariableDimensionHistogram< TMeasurement, TFrequencyContainer >::Iterator | |
| itk::VariableLengthVector< TValueType > | VariableLengthVector is intended to reperesent 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 |
| vcl_simple_alloc< T, Alloc > | |
| 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::VectorConfidenceConnectedImageFilter< TInputImage, TOutputImage > | |
| itk::VectorConnectedComponentImageFilter< TInputImage, TOutputImage, TMaskImage > | |
| itk::VectorContainer< TElementIdentifier, TElement > | |
| itk::VectorContainer< TElementIdentifier, TElement >::ConstIterator | |
| itk::VectorContainer< TElementIdentifier, TElement >::Iterator | |
| 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, TPixelType > | Base class for all vector image interpolaters |
| itk::VectorLinearInterpolateImageFunction< TInputImage, TCoordRep > | Linearly interpolate 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::Version | Track 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::VersorRigid3DTransformOptimizer | Implement a gradient descent optimizer for the VersorRigid3DTransform parameter space |
| itk::VersorTransform< TScalarType > | |
| itk::VersorTransformOptimizer | Implement 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 > | |
| vnl_fft_3d< T > | |
| vnl_vector | |
| itk::VnlFFTComplexConjugateToRealImageFilter< TPixel, Dimension > | |
| itk::VnlFFTRealToComplexConjugateImageFilter< TPixel, Dimension > | |
| itk::VolumeSplineKernelTransform< TScalarType, NDimensions > | |
| itk::VoronoiDiagram2D< TCoordType > | Implements the 2-Dimensional Voronoi Diagram |
| itk::VoronoiDiagram2D< TCoordType >::VoronoiEdge | |
| itk::VoronoiDiagram2DGenerator< TCoordType > | Implement the Sweep Line Algorithm for the construction of the 2D Voronoi Diagram |
| itk::VoronoiPartitioningImageFilter< TInputImage, TOutputImage > | |
| itk::VoronoiSegmentationImageFilter< TInputImage, TOutputImage, TBinaryPriorImage > | |
| itk::VoronoiSegmentationImageFilterBase< TInputImage, TOutputImage, TBinaryPriorImage > | |
| 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::VTKImageExport< TInputImage > | Connect the end of an ITK image pipeline to a VTK pipeline |
| itk::VTKImageExportBase | Superclass for VTKImageExport instantiations |
| itk::VTKImageExportBase::CallbackTypeProxy | |
| itk::VTKImageImport< TOutputImage > | Connect the end of an VTK pipeline to an ITK image pipeline |
| itk::VTKImageIO | ImageIO class for reading VTK images |
| itk::VTKImageIOFactory | Create 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::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 | |
| WatershedSegmenter | |
| WatershedSegmentTreeGenerator | |
| 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 computed 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::WeightedMeanCalculator< TSample > | Calculates sample mean where each measurement vector has associated weight value |
| itk::Statistics::WeightSetBase< TMeasurementVector, TTargetVector > | |
| itk::Function::WelchWindowFunction< VRadius, TInput, TOutput > | Window function for sinc interpolation.
![\[ w(x) = 1 - ( \frac{x^2}{m^2} ) \]](form_191.png)
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| itk::WhiteTopHatImageFilter< TInputImage, TOutputImage, TKernel > | White top hat extract local maxima that are larger than the structuring element |
| itk::Win32OutputWindow | Collect error and debug messages on Win32-based systems |
| itk::WindowedSincInterpolateImageFunction< TInputImage, VRadius, TWindowFunction, TBoundaryCondition, TCoordRep > | Use the windowed sinc function to interpolate |
| itk::WrapPadImageFilter< TInputImage, TOutputImage > | Increase the image size by padding with replicants of the input image value |
| itk::XMLFileOutputWindow | Messages sent from the system are sent to a file with each message enclosed by XML tags |
| itk::XMLFilterWatcher | Simple 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 |
