ITK
5.2.0
Insight Toolkit
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#include <itkBayesianClassifierInitializationImageFilter.h>
Static Public Member Functions | |
static Pointer | New () |
Static Public Member Functions inherited from itk::ImageToImageFilter< TInputImage, VectorImage< TProbabilityPrecisionType, TInputImage::ImageDimension > > | |
static void | SetGlobalDefaultDirectionTolerance (double) |
static double | GetGlobalDefaultDirectionTolerance () |
static void | SetGlobalDefaultCoordinateTolerance (double) |
static double | GetGlobalDefaultCoordinateTolerance () |
Static Public Member Functions inherited from itk::Object | |
static bool | GetGlobalWarningDisplay () |
static void | GlobalWarningDisplayOff () |
static void | GlobalWarningDisplayOn () |
static Pointer | New () |
static void | SetGlobalWarningDisplay (bool val) |
Static Public Member Functions inherited from itk::LightObject | |
static void | BreakOnError () |
static Pointer | New () |
This filter is intended to be used as a helper class to initialize the BayesianClassifierImageFilter.
Definition at line 77 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::ConstPointer = SmartPointer<const Self> |
Definition at line 94 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::InputImageIteratorType = ImageRegionConstIterator<InputImageType> |
Input image iterators
Definition at line 103 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::InputImageType = TInputImage |
Definition at line 85 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::InputPixelType = typename InputImageType::PixelType |
Pixel types.
Definition at line 106 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::MeasurementVectorType = Vector<InputPixelType, 1> |
Type of the Measurement
Definition at line 118 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::MembershipFunctionContainerPointer = typename MembershipFunctionContainerType::Pointer |
Definition at line 126 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::MembershipFunctionContainerType = VectorContainer<unsigned int, MembershipFunctionPointer> |
Membership function container
Definition at line 125 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::MembershipFunctionPointer = typename MembershipFunctionType::Pointer |
Definition at line 122 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::MembershipFunctionType = Statistics::MembershipFunctionBase<MeasurementVectorType> |
Type of the density functions
Definition at line 121 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::MembershipImageIteratorType = ImageRegionIterator<MembershipImageType> |
Definition at line 115 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::MembershipImagePointer = typename MembershipImageType::Pointer |
Definition at line 114 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::MembershipImageType = VectorImage<ProbabilityPrecisionType, Self::Dimension> |
Image Type and Pixel type for the images representing the membership of a pixel to a particular class. This image has arrays as pixels, the number of elements in the array is the same as the number of classes to be used.
Definition at line 112 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::MembershipPixelType = typename MembershipImageType::PixelType |
Definition at line 113 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::OutputImageType = VectorImage<ProbabilityPrecisionType, Self::Dimension> |
Definition at line 91 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::OutputPixelType = typename OutputImageType::PixelType |
Definition at line 107 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::Pointer = SmartPointer<Self> |
Definition at line 93 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::ProbabilityPrecisionType = TProbabilityPrecisionType |
Definition at line 86 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::Self = BayesianClassifierInitializationImageFilter |
Standard class type aliases.
Definition at line 84 of file itkBayesianClassifierInitializationImageFilter.h.
using itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >::Superclass = ImageToImageFilter<InputImageType, OutputImageType> |
Definition at line 92 of file itkBayesianClassifierInitializationImageFilter.h.
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protected |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
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overrideprotecteddefault |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
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virtual |
Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.
Reimplemented from itk::Object.
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overrideprotectedvirtual |
Here is where the prior and membership probability vector images are created.
Reimplemented from itk::ProcessObject.
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overridevirtual |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
Reimplemented from itk::ProcessObject.
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virtual |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
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virtual |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
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virtual |
Run-time type information (and related methods).
Reimplemented from itk::ImageToImageFilter< TInputImage, VectorImage< TProbabilityPrecisionType, TInputImage::ImageDimension > >.
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virtual |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
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protectedvirtual |
Initialize the membership functions. This will be called only if the membership function hasn't already been set. This method initializes membership functions using Gaussian density functions centered around the means computed using Kmeans.
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static |
Method for creation through the object factory.
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overrideprotectedvirtual |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
Reimplemented from itk::ProcessObject.
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virtual |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
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virtual |
Set/Get methods for the number of classes. The user must supply this.
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staticconstexpr |
Dimension of the input image
Definition at line 89 of file itkBayesianClassifierInitializationImageFilter.h.
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private |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
Definition at line 179 of file itkBayesianClassifierInitializationImageFilter.h.
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private |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
Definition at line 177 of file itkBayesianClassifierInitializationImageFilter.h.
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private |
Method to set/get the density functions. Here you can set a vector container of density functions. If no density functions are specified, the filter will create ones for you. These default density functions are Gaussian density functions centered around the K-means of the input image.
Definition at line 176 of file itkBayesianClassifierInitializationImageFilter.h.