ITK  5.2.0
Insight Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Static Public Attributes | List of all members
itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType > Class Template Reference

#include <itkBayesianClassifierImageFilter.h>

+ Inheritance diagram for itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >:
+ Collaboration diagram for itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >:

Public Types

using ConstPointer = SmartPointer< const Self >
 
using DataObjectPointer = typename Superclass::DataObjectPointer
 
using DecisionRulePointer = DecisionRuleType::Pointer
 
using DecisionRuleType = Statistics::MaximumDecisionRule
 
using ExtractedComponentImageType = itk::Image< TPosteriorsPrecisionType, Self::Dimension >
 
using ImageRegionType = typename InputImageType::RegionType
 
using InputImageIteratorType = ImageRegionConstIterator< InputImageType >
 
using InputImagePointer = typename InputImageType::ConstPointer
 
using InputImageType = typename Superclass::InputImageType
 
using InputPixelType = typename InputImageType::PixelType
 
using MembershipImageIteratorType = ImageRegionConstIterator< MembershipImageType >
 
using MembershipImagePointer = typename MembershipImageType::Pointer
 
using MembershipImageType = TInputVectorImage
 
using MembershipPixelType = typename MembershipImageType::PixelType
 
using OutputImageIteratorType = ImageRegionIterator< OutputImageType >
 
using OutputImagePointer = typename OutputImageType::Pointer
 
using OutputImageType = Image< TLabelsType, Self::Dimension >
 
using OutputPixelType = typename OutputImageType::PixelType
 
using Pointer = SmartPointer< Self >
 
using PosteriorsImageIteratorType = ImageRegionIterator< PosteriorsImageType >
 
using PosteriorsImagePointer = typename PosteriorsImageType::Pointer
 
using PosteriorsImageType = VectorImage< TPosteriorsPrecisionType, Self::Dimension >
 
using PosteriorsPixelType = typename PosteriorsImageType::PixelType
 
using PriorsImageIteratorType = ImageRegionConstIterator< PriorsImageType >
 
using PriorsImagePointer = typename PriorsImageType::Pointer
 
using PriorsImageType = VectorImage< TPriorsPrecisionType, Self::Dimension >
 
using PriorsPixelType = typename PriorsImageType::PixelType
 
using Self = BayesianClassifierImageFilter
 
using SmoothingFilterPointer = typename SmoothingFilterType::Pointer
 
using SmoothingFilterType = ImageToImageFilter< ExtractedComponentImageType, ExtractedComponentImageType >
 
using Superclass = ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > >
 
- Public Types inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage ::ImageDimension > >
using ConstPointer = SmartPointer< const Self >
 
using InputImageConstPointer = typename InputImageType::ConstPointer
 
using InputImagePixelType = typename InputImageType::PixelType
 
using InputImagePointer = typename InputImageType::Pointer
 
using InputImageRegionType = typename InputImageType::RegionType
 
using InputImageType = TInputVectorImage
 
using OutputImagePixelType = typename Superclass::OutputImagePixelType
 
using OutputImageRegionType = typename Superclass::OutputImageRegionType
 
using Pointer = SmartPointer< Self >
 
using Self = ImageToImageFilter
 
using Superclass = ImageSource< Image< TLabelsType, TInputVectorImage ::ImageDimension > >
 
- Public Types inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage ::ImageDimension > >
using ConstPointer = SmartPointer< const Self >
 
using DataObjectIdentifierType = Superclass::DataObjectIdentifierType
 
using DataObjectPointer = DataObject::Pointer
 
using DataObjectPointerArraySizeType = Superclass::DataObjectPointerArraySizeType
 
using OutputImagePixelType = typename OutputImageType::PixelType
 
using OutputImagePointer = typename OutputImageType::Pointer
 
using OutputImageRegionType = typename OutputImageType::RegionType
 
using OutputImageType = Image< TLabelsType, TInputVectorImage ::ImageDimension >
 
using Pointer = SmartPointer< Self >
 
using Self = ImageSource
 
using Superclass = ProcessObject
 
- Public Types inherited from itk::ProcessObject
using ConstPointer = SmartPointer< const Self >
 
using DataObjectIdentifierType = DataObject::DataObjectIdentifierType
 
using DataObjectPointer = DataObject::Pointer
 
using DataObjectPointerArray = std::vector< DataObjectPointer >
 
using DataObjectPointerArraySizeType = DataObjectPointerArray::size_type
 
using MultiThreaderType = MultiThreaderBase
 
using NameArray = std::vector< DataObjectIdentifierType >
 
using Pointer = SmartPointer< Self >
 
using Self = ProcessObject
 
using Superclass = Object
 
- Public Types inherited from itk::Object
using ConstPointer = SmartPointer< const Self >
 
using Pointer = SmartPointer< Self >
 
using Self = Object
 
using Superclass = LightObject
 
- Public Types inherited from itk::LightObject
using ConstPointer = SmartPointer< const Self >
 
using Pointer = SmartPointer< Self >
 
using Self = LightObject
 

Public Member Functions

virtual ::itk::LightObject::Pointer CreateAnother () const
 
virtual const char * GetNameOfClass () const
 
- Public Member Functions inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage ::ImageDimension > >
const InputImageTypeGetInput () const
 
const InputImageTypeGetInput (unsigned int idx) const
 
void PopBackInput () override
 
void PopFrontInput () override
 
virtual void PushBackInput (const InputImageType *image)
 
virtual void PushFrontInput (const InputImageType *image)
 
virtual void SetInput (const DataObjectIdentifierType &key, DataObject *input)
 
virtual void SetInput (const InputImageType *image)
 
virtual void SetInput (unsigned int, const TInputVectorImage *image)
 
virtual void SetCoordinateTolerance (double _arg)
 
virtual double GetCoordinateTolerance () const
 
virtual void SetDirectionTolerance (double _arg)
 
virtual double GetDirectionTolerance () const
 
- Public Member Functions inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage ::ImageDimension > >
OutputImageTypeGetOutput ()
 
const OutputImageTypeGetOutput () const
 
OutputImageTypeGetOutput (unsigned int idx)
 
virtual void GraftOutput (DataObject *output)
 
virtual void GraftOutput (const DataObjectIdentifierType &key, DataObject *output)
 
virtual void GraftNthOutput (unsigned int idx, DataObject *output)
 
ProcessObject::DataObjectPointer MakeOutput (ProcessObject::DataObjectPointerArraySizeType idx) override
 
ProcessObject::DataObjectPointer MakeOutput (const ProcessObject::DataObjectIdentifierType &) override
 
- Public Member Functions inherited from itk::ProcessObject
virtual void AbortGenerateDataOff ()
 
virtual void AbortGenerateDataOn ()
 
virtual void EnlargeOutputRequestedRegion (DataObject *)
 
virtual const bool & GetAbortGenerateData () const
 
DataObjectPointerArray GetIndexedInputs ()
 
DataObjectPointerArray GetIndexedOutputs ()
 
NameArray GetInputNames () const
 
DataObjectPointerArray GetInputs ()
 
DataObjectPointerArraySizeType GetNumberOfIndexedInputs () const
 
DataObjectPointerArraySizeType GetNumberOfIndexedOutputs () const
 
DataObjectPointerArraySizeType GetNumberOfInputs () const
 
DataObjectPointerArraySizeType GetNumberOfOutputs () const
 
virtual DataObjectPointerArraySizeType GetNumberOfValidRequiredInputs () const
 
NameArray GetOutputNames () const
 
DataObjectPointerArray GetOutputs ()
 
virtual float GetProgress () const
 
NameArray GetRequiredInputNames () const
 
bool HasInput (const DataObjectIdentifierType &key) const
 
bool HasOutput (const DataObjectIdentifierType &key) const
 
void IncrementProgress (float increment)
 
virtual void PropagateRequestedRegion (DataObject *output)
 
virtual void ResetPipeline ()
 
virtual void SetAbortGenerateData (bool _arg)
 
virtual void Update ()
 
virtual void UpdateLargestPossibleRegion ()
 
virtual void UpdateOutputData (DataObject *output)
 
virtual void UpdateOutputInformation ()
 
void UpdateProgress (float progress)
 
virtual void SetReleaseDataFlag (bool flag)
 
virtual bool GetReleaseDataFlag () const
 
void ReleaseDataFlagOn ()
 
void ReleaseDataFlagOff ()
 
virtual void SetReleaseDataBeforeUpdateFlag (bool _arg)
 
virtual const bool & GetReleaseDataBeforeUpdateFlag () const
 
virtual void ReleaseDataBeforeUpdateFlagOn ()
 
virtual void ReleaseDataBeforeUpdateFlagOff ()
 
virtual void SetNumberOfWorkUnits (ThreadIdType _arg)
 
virtual const ThreadIdTypeGetNumberOfWorkUnits () const
 
MultiThreaderTypeGetMultiThreader () const
 
void SetMultiThreader (MultiThreaderType *threader)
 
virtual void PrepareOutputs ()
 
- Public Member Functions inherited from itk::Object
unsigned long AddObserver (const EventObject &event, Command *)
 
unsigned long AddObserver (const EventObject &event, Command *) const
 
virtual void DebugOff () const
 
virtual void DebugOn () const
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary ()
 
const MetaDataDictionaryGetMetaDataDictionary () const
 
virtual ModifiedTimeType GetMTime () const
 
virtual const TimeStampGetTimeStamp () const
 
bool HasObserver (const EventObject &event) const
 
void InvokeEvent (const EventObject &)
 
void InvokeEvent (const EventObject &) const
 
virtual void Modified () const
 
void Register () const override
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
void SetDebug (bool debugFlag) const
 
void SetReferenceCount (int) override
 
void UnRegister () const noexcept override
 
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
 
void SetMetaDataDictionary (MetaDataDictionary &&rrhs)
 
virtual void SetObjectName (std::string _arg)
 
virtual const std::string & GetObjectName () const
 
- Public Member Functions inherited from itk::LightObject
virtual void Delete ()
 
virtual int GetReferenceCount () const
 
 itkCloneMacro (Self)
 
void Print (std::ostream &os, Indent indent=0) const
 

Static Public Member Functions

static Pointer New ()
 
- Static Public Member Functions inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage ::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 flag)
 
- Static Public Member Functions inherited from itk::LightObject
static void BreakOnError ()
 
static Pointer New ()
 

Static Public Attributes

static constexpr unsigned int Dimension = InputImageType ::ImageDimension
 
- Static Public Attributes inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage ::ImageDimension > >
static constexpr unsigned int InputImageDimension
 
static constexpr unsigned int OutputImageDimension
 
- Static Public Attributes inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage ::ImageDimension > >
static constexpr unsigned int OutputImageDimension
 
using DataObjectPointerArraySizeType = ProcessObject::DataObjectPointerArraySizeType
 
bool m_UserProvidedPriors { false }
 
bool m_UserProvidedSmoothingFilter { false }
 
SmoothingFilterPointer m_SmoothingFilter
 
unsigned int m_NumberOfSmoothingIterations { 0 }
 
void SetSmoothingFilter (SmoothingFilterType *)
 
virtual SmoothingFilterPointer GetSmoothingFilter () const
 
virtual void SetPriors (const PriorsImageType *)
 
virtual void SetNumberOfSmoothingIterations (unsigned int _arg)
 
virtual unsigned int GetNumberOfSmoothingIterations () const
 
DataObjectPointer MakeOutput (DataObjectPointerArraySizeType idx) override
 
 BayesianClassifierImageFilter ()
 
 ~BayesianClassifierImageFilter () override=default
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
void GenerateData () override
 
void GenerateOutputInformation () override
 
virtual void ComputeBayesRule ()
 
virtual void NormalizeAndSmoothPosteriors ()
 
virtual void ClassifyBasedOnPosteriors ()
 
PosteriorsImageTypeGetPosteriorImage ()
 

Additional Inherited Members

- Protected Types inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage ::ImageDimension > >
using InputToOutputRegionCopierType = ImageToImageFilterDetail::ImageRegionCopier< Self::OutputImageDimension, Self::InputImageDimension >
 
using OutputToInputRegionCopierType = ImageToImageFilterDetail::ImageRegionCopier< Self::InputImageDimension, Self::OutputImageDimension >
 
- Protected Member Functions inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage ::ImageDimension > >
void PushBackInput (const DataObject *input) override
 
void PushFrontInput (const DataObject *input) override
 
 ImageToImageFilter ()
 
 ~ImageToImageFilter () override=default
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
void VerifyInputInformation () ITKv5_CONST override
 
void GenerateInputRequestedRegion () override
 
virtual void CallCopyOutputRegionToInputRegion (InputImageRegionType &destRegion, const OutputImageRegionType &srcRegion)
 
virtual void CallCopyInputRegionToOutputRegion (OutputImageRegionType &destRegion, const InputImageRegionType &srcRegion)
 
- Protected Member Functions inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage ::ImageDimension > >
 ImageSource ()
 
 ~ImageSource () override=default
 
void GenerateData () override
 
void ClassicMultiThread (ThreadFunctionType callbackFunction)
 
virtual void ThreadedGenerateData (const OutputImageRegionType &outputRegionForThread, ThreadIdType threadId)
 
virtual void DynamicThreadedGenerateData (const OutputImageRegionType &outputRegionForThread)
 
virtual void AllocateOutputs ()
 
virtual void BeforeThreadedGenerateData ()
 
virtual void AfterThreadedGenerateData ()
 
virtual const ImageRegionSplitterBaseGetImageRegionSplitter () const
 
virtual unsigned int SplitRequestedRegion (unsigned int i, unsigned int pieces, OutputImageRegionType &splitRegion)
 
virtual bool GetDynamicMultiThreading () const
 
virtual void SetDynamicMultiThreading (bool _arg)
 
virtual void DynamicMultiThreadingOn ()
 
virtual void DynamicMultiThreadingOff ()
 
- Protected Member Functions inherited from itk::ProcessObject
 ProcessObject ()
 
 ~ProcessObject () override
 
DataObjectGetInput (const DataObjectIdentifierType &key)
 
const DataObjectGetInput (const DataObjectIdentifierType &key) const
 
DataObjectGetInput (DataObjectPointerArraySizeType idx)
 
const DataObjectGetInput (DataObjectPointerArraySizeType idx) const
 
virtual void SetInput (const DataObjectIdentifierType &key, DataObject *input)
 
virtual void SetNthInput (DataObjectPointerArraySizeType num, DataObject *input)
 
virtual void AddInput (DataObject *input)
 
virtual void RemoveInput (const DataObjectIdentifierType &key)
 
virtual void RemoveInput (DataObjectPointerArraySizeType)
 
DataObjectGetPrimaryInput ()
 
const DataObjectGetPrimaryInput () const
 
virtual void SetPrimaryInputName (const DataObjectIdentifierType &key)
 
virtual const char * GetPrimaryInputName () const
 
virtual void SetPrimaryInput (DataObject *input)
 
void SetNumberOfIndexedInputs (DataObjectPointerArraySizeType num)
 
virtual void SetNumberOfRequiredInputs (DataObjectPointerArraySizeType)
 
virtual const DataObjectPointerArraySizeTypeGetNumberOfRequiredInputs () const
 
bool RemoveRequiredInputName (const DataObjectIdentifierType &)
 
bool IsRequiredInputName (const DataObjectIdentifierType &) const
 
void SetRequiredInputNames (const NameArray &)
 
bool AddRequiredInputName (const DataObjectIdentifierType &)
 
bool AddRequiredInputName (const DataObjectIdentifierType &, DataObjectPointerArraySizeType idx)
 
void AddOptionalInputName (const DataObjectIdentifierType &)
 
void AddOptionalInputName (const DataObjectIdentifierType &, DataObjectPointerArraySizeType idx)
 
DataObjectGetOutput (const DataObjectIdentifierType &key)
 
const DataObjectGetOutput (const DataObjectIdentifierType &key) const
 
virtual void SetPrimaryOutputName (const DataObjectIdentifierType &key)
 
virtual const char * GetPrimaryOutputName () const
 
DataObjectGetOutput (DataObjectPointerArraySizeType idx)
 
const DataObjectGetOutput (DataObjectPointerArraySizeType idx) const
 
virtual void SetOutput (const DataObjectIdentifierType &key, DataObject *output)
 
virtual void RemoveOutput (const DataObjectIdentifierType &key)
 
DataObjectGetPrimaryOutput ()
 
const DataObjectGetPrimaryOutput () const
 
virtual void SetPrimaryOutput (DataObject *output)
 
virtual void SetNthOutput (DataObjectPointerArraySizeType num, DataObject *output)
 
virtual void AddOutput (DataObject *output)
 
virtual void RemoveOutput (DataObjectPointerArraySizeType idx)
 
virtual void SetNumberOfRequiredOutputs (DataObjectPointerArraySizeType _arg)
 
virtual const DataObjectPointerArraySizeTypeGetNumberOfRequiredOutputs () const
 
void SetNumberOfIndexedOutputs (DataObjectPointerArraySizeType num)
 
DataObjectIdentifierType MakeNameFromInputIndex (DataObjectPointerArraySizeType idx) const
 
DataObjectIdentifierType MakeNameFromOutputIndex (DataObjectPointerArraySizeType idx) const
 
DataObjectPointerArraySizeType MakeIndexFromInputName (const DataObjectIdentifierType &name) const
 
DataObjectPointerArraySizeType MakeIndexFromOutputName (const DataObjectIdentifierType &name) const
 
bool IsIndexedInputName (const DataObjectIdentifierType &) const
 
bool IsIndexedOutputName (const DataObjectIdentifierType &) const
 
virtual void VerifyPreconditions () ITKv5_CONST
 
virtual void GenerateOutputRequestedRegion (DataObject *output)
 
virtual void PropagateResetPipeline ()
 
virtual void ReleaseInputs ()
 
virtual void CacheInputReleaseDataFlags ()
 
virtual void RestoreInputReleaseDataFlags ()
 
virtual bool GetThreaderUpdateProgress () const
 
virtual void ThreaderUpdateProgressOn ()
 
virtual void ThreaderUpdateProgressOff ()
 
virtual void SetThreaderUpdateProgress (bool arg)
 
- Protected Member Functions inherited from itk::Object
 Object ()
 
 ~Object () override
 
bool PrintObservers (std::ostream &os, Indent indent) const
 
virtual void SetTimeStamp (const TimeStamp &time)
 
- Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer InternalClone () const
 
 LightObject ()
 
virtual void PrintHeader (std::ostream &os, Indent indent) const
 
virtual void PrintTrailer (std::ostream &os, Indent indent) const
 
virtual ~LightObject ()
 
- Static Protected Member Functions inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage ::ImageDimension > >
static const ImageRegionSplitterBaseGetGlobalDefaultSplitter ()
 
static ITK_THREAD_RETURN_FUNCTION_CALL_CONVENTION ThreaderCallback (void *arg)
 
- Static Protected Member Functions inherited from itk::ProcessObject
static constexpr float progressFixedToFloat (uint32_t fixed)
 
static uint32_t progressFloatToFixed (float f)
 
- Protected Attributes inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage ::ImageDimension > >
bool m_DynamicMultiThreading
 
- Protected Attributes inherited from itk::ProcessObject
bool m_Updating
 
TimeStamp m_OutputInformationMTime
 
- Protected Attributes inherited from itk::LightObject
std::atomic< int > m_ReferenceCount
 

Detailed Description

template<typename TInputVectorImage, typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
class itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >

Performs Bayesian Classification on an image.

Inputs and Outputs
The input to this filter is an itk::VectorImage that represents pixel memberships to 'n' classes. This image is conveniently generated by the BayesianClassifierInitializationImageFilter. You may use that filter to generate the membership images or specify your own.
The output of the filter is a label map (an image of unsigned char's is the default.) with pixel values indicating the classes they correspond to. Pixels with intensity 0 belong to the 0th class, 1 belong to the 1st class etc.... The classification is done by applying a Maximum decision rule to the posterior image.
Parameters
The filter optionally allows you to specify a prior image as well. The prior image, if specified must be a VectorImage with as many components as the number of classes. The posterior image is then generated by multiplying the prior image with the membership image. If the prior image is not specified, the posterior image is the same as the membership image. Another way to look at it is that the priors default to having a uniform distribution over the number of classes. Posterior membership of a pixel = Prior * Membership
The filter optionally accepts a smoothing filter and number of iterations associated with the smoothing filter. The philosophy is that the filter allows you to iteratively smooth the posteriors prior to applying the decision rule. It is hoped that this would yield a better classification. The user will need to plug in his own smoothing filter with all the parameters set.
Template parameters
InputVectorImage, datatype of the output labelmap, precision of the posterior image, precision of the prior image.
Author
John Melonakos, Georgia Tech
Note
This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.
See also
VectorImage
BayesianClassifierInitializationImageFilter
Examples
Examples/Statistics/BayesianClassifier.cxx.

Definition at line 84 of file itkBayesianClassifierImageFilter.h.

Member Typedef Documentation

◆ ConstPointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::ConstPointer = SmartPointer<const Self>

Definition at line 95 of file itkBayesianClassifierImageFilter.h.

◆ DataObjectPointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::DataObjectPointer = typename Superclass::DataObjectPointer

Definition at line 152 of file itkBayesianClassifierImageFilter.h.

◆ DataObjectPointerArraySizeType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::DataObjectPointerArraySizeType = ProcessObject::DataObjectPointerArraySizeType

This is overloaded to create the Posteriors output image.

Definition at line 179 of file itkBayesianClassifierImageFilter.h.

◆ DecisionRulePointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::DecisionRulePointer = DecisionRuleType::Pointer

Definition at line 150 of file itkBayesianClassifierImageFilter.h.

◆ DecisionRuleType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::DecisionRuleType = Statistics::MaximumDecisionRule

Decision rule to use for defining the label.

Definition at line 149 of file itkBayesianClassifierImageFilter.h.

◆ ExtractedComponentImageType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::ExtractedComponentImageType = itk::Image<TPosteriorsPrecisionType, Self::Dimension>

An image from a single component of the Posterior.

Definition at line 155 of file itkBayesianClassifierImageFilter.h.

◆ ImageRegionType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::ImageRegionType = typename InputImageType::RegionType

Definition at line 112 of file itkBayesianClassifierImageFilter.h.

◆ InputImageIteratorType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::InputImageIteratorType = ImageRegionConstIterator<InputImageType>

Input and Output image iterators.

Definition at line 115 of file itkBayesianClassifierImageFilter.h.

◆ InputImagePointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::InputImagePointer = typename InputImageType::ConstPointer

Definition at line 110 of file itkBayesianClassifierImageFilter.h.

◆ InputImageType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::InputImageType = typename Superclass::InputImageType

Input and Output image types.

Definition at line 104 of file itkBayesianClassifierImageFilter.h.

◆ InputPixelType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::InputPixelType = typename InputImageType::PixelType

Pixel types.

Definition at line 119 of file itkBayesianClassifierImageFilter.h.

◆ MembershipImageIteratorType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MembershipImageIteratorType = ImageRegionConstIterator<MembershipImageType>

Definition at line 137 of file itkBayesianClassifierImageFilter.h.

◆ MembershipImagePointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MembershipImagePointer = typename MembershipImageType::Pointer

Definition at line 136 of file itkBayesianClassifierImageFilter.h.

◆ MembershipImageType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MembershipImageType = TInputVectorImage

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 134 of file itkBayesianClassifierImageFilter.h.

◆ MembershipPixelType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MembershipPixelType = typename MembershipImageType::PixelType

Definition at line 135 of file itkBayesianClassifierImageFilter.h.

◆ OutputImageIteratorType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::OutputImageIteratorType = ImageRegionIterator<OutputImageType>

Definition at line 116 of file itkBayesianClassifierImageFilter.h.

◆ OutputImagePointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::OutputImagePointer = typename OutputImageType::Pointer

Definition at line 111 of file itkBayesianClassifierImageFilter.h.

◆ OutputImageType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::OutputImageType = Image<TLabelsType, Self::Dimension>

Definition at line 109 of file itkBayesianClassifierImageFilter.h.

◆ OutputPixelType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::OutputPixelType = typename OutputImageType::PixelType

Definition at line 120 of file itkBayesianClassifierImageFilter.h.

◆ Pointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::Pointer = SmartPointer<Self>

Definition at line 94 of file itkBayesianClassifierImageFilter.h.

◆ PosteriorsImageIteratorType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PosteriorsImageIteratorType = ImageRegionIterator<PosteriorsImageType>

Definition at line 146 of file itkBayesianClassifierImageFilter.h.

◆ PosteriorsImagePointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PosteriorsImagePointer = typename PosteriorsImageType::Pointer

Definition at line 145 of file itkBayesianClassifierImageFilter.h.

◆ PosteriorsImageType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PosteriorsImageType = VectorImage<TPosteriorsPrecisionType, Self::Dimension>

Image Type and Pixel type for the images representing the Posterior probability of a pixel belonging 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 143 of file itkBayesianClassifierImageFilter.h.

◆ PosteriorsPixelType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PosteriorsPixelType = typename PosteriorsImageType::PixelType

Definition at line 144 of file itkBayesianClassifierImageFilter.h.

◆ PriorsImageIteratorType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PriorsImageIteratorType = ImageRegionConstIterator<PriorsImageType>

Definition at line 129 of file itkBayesianClassifierImageFilter.h.

◆ PriorsImagePointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PriorsImagePointer = typename PriorsImageType::Pointer

Definition at line 128 of file itkBayesianClassifierImageFilter.h.

◆ PriorsImageType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PriorsImageType = VectorImage<TPriorsPrecisionType, Self::Dimension>

Image Type and Pixel type for the images representing the Prior probability of a pixel belonging 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 126 of file itkBayesianClassifierImageFilter.h.

◆ PriorsPixelType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PriorsPixelType = typename PriorsImageType::PixelType

Definition at line 127 of file itkBayesianClassifierImageFilter.h.

◆ Self

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::Self = BayesianClassifierImageFilter

Standard class type aliases.

Definition at line 91 of file itkBayesianClassifierImageFilter.h.

◆ SmoothingFilterPointer

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::SmoothingFilterPointer = typename SmoothingFilterType::Pointer

Definition at line 160 of file itkBayesianClassifierImageFilter.h.

◆ SmoothingFilterType

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::SmoothingFilterType = ImageToImageFilter<ExtractedComponentImageType, ExtractedComponentImageType>

Optional Smoothing filter that will be applied to the Posteriors.

Definition at line 158 of file itkBayesianClassifierImageFilter.h.

◆ Superclass

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
using itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::Superclass = ImageToImageFilter<TInputVectorImage, Image<TLabelsType, TInputVectorImage::ImageDimension> >

Definition at line 92 of file itkBayesianClassifierImageFilter.h.

Constructor & Destructor Documentation

◆ BayesianClassifierImageFilter()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::BayesianClassifierImageFilter ( )
protected

This is overloaded to create the Posteriors output image.

◆ ~BayesianClassifierImageFilter()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::~BayesianClassifierImageFilter ( )
overrideprotecteddefault

This is overloaded to create the Posteriors output image.

Member Function Documentation

◆ ClassifyBasedOnPosteriors()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::ClassifyBasedOnPosteriors ( )
protectedvirtual

Compute the labeled map based on the Maximum rule applied to the posteriors.

◆ ComputeBayesRule()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::ComputeBayesRule ( )
protectedvirtual

Compute the posteriors using the Bayes rule. If no priors are available, then the posteriors are just a copy of the memberships. Computes the labeled map for all combinations of conditions.

◆ CreateAnother()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual::itk::LightObject::Pointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::CreateAnother ( ) const
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.

◆ GenerateData()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GenerateData ( )
overrideprotectedvirtual

This is overloaded to create the Posteriors output image.

Reimplemented from itk::ProcessObject.

◆ GenerateOutputInformation()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GenerateOutputInformation ( )
overrideprotectedvirtual

This is overloaded to create the Posteriors output image.

Reimplemented from itk::ProcessObject.

◆ GetNameOfClass()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual const char* itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GetNameOfClass ( ) const
virtual

Run-time type information (and related methods).

Reimplemented from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage ::ImageDimension > >.

◆ GetNumberOfSmoothingIterations()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual unsigned int itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GetNumberOfSmoothingIterations ( ) const
virtual

This is overloaded to create the Posteriors output image.

◆ GetPosteriorImage()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
PosteriorsImageType* itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GetPosteriorImage ( )
protected

Get the Posteriors Image.

◆ GetSmoothingFilter()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual SmoothingFilterPointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GetSmoothingFilter ( ) const
virtual

This is overloaded to create the Posteriors output image.

◆ MakeOutput()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
DataObjectPointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MakeOutput ( DataObjectPointerArraySizeType  idx)
overridevirtual

This is overloaded to create the Posteriors output image.

Reimplemented from itk::ProcessObject.

◆ New()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
static Pointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::New ( )
static

Method for creation through the object factory.

◆ NormalizeAndSmoothPosteriors()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::NormalizeAndSmoothPosteriors ( )
protectedvirtual

Normalize the posteriors and smooth them using a user-provided.

◆ PrintSelf()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
overrideprotectedvirtual

This is overloaded to create the Posteriors output image.

Reimplemented from itk::ProcessObject.

◆ SetNumberOfSmoothingIterations()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::SetNumberOfSmoothingIterations ( unsigned int  _arg)
virtual

Number of iterations to apply the smoothing filter.

◆ SetPriors()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::SetPriors ( const PriorsImageType )
virtual

Set the priors image.

◆ SetSmoothingFilter()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::SetSmoothingFilter ( SmoothingFilterType )

Set/Get the smoothing filter that may optionally be applied to the posterior image.

Member Data Documentation

◆ Dimension

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
constexpr unsigned int itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::Dimension = InputImageType ::ImageDimension
staticconstexpr

Dimension of the input image.

Definition at line 107 of file itkBayesianClassifierImageFilter.h.

◆ m_NumberOfSmoothingIterations

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
unsigned int itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::m_NumberOfSmoothingIterations { 0 }
private

This is overloaded to create the Posteriors output image.

Definition at line 235 of file itkBayesianClassifierImageFilter.h.

◆ m_SmoothingFilter

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
SmoothingFilterPointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::m_SmoothingFilter
private

This is overloaded to create the Posteriors output image.

Definition at line 233 of file itkBayesianClassifierImageFilter.h.

◆ m_UserProvidedPriors

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
bool itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::m_UserProvidedPriors { false }
private

This is overloaded to create the Posteriors output image.

Definition at line 229 of file itkBayesianClassifierImageFilter.h.

◆ m_UserProvidedSmoothingFilter

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
bool itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::m_UserProvidedSmoothingFilter { false }
private

This is overloaded to create the Posteriors output image.

Definition at line 231 of file itkBayesianClassifierImageFilter.h.


The documentation for this class was generated from the following file: