itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType > Class Template Reference

#include <itkBayesianClassifierImageFilter.h>

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.

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	DataObjectPointerArraySizeType = ProcessObject::DataObjectPointerArraySizeType
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	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	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
const char *	GetNameOfClass () const override
DataObjectPointer	MakeOutput (DataObjectPointerArraySizeType idx) override
virtual void	SetPriors (const PriorsImageType *)
void	SetSmoothingFilter (SmoothingFilterType *)
virtual SmoothingFilterPointer	GetSmoothingFilter () const
virtual void	SetNumberOfSmoothingIterations (unsigned int _arg)
virtual unsigned int	GetNumberOfSmoothingIterations () const
Public Member Functions inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > >
const InputImageType *	GetInput () const
const InputImageType *	GetInput (unsigned int idx) const
const char *	GetNameOfClass () const override
void	PopBackInput () override
void	PopFrontInput () override
virtual void	PushBackInput (const InputImageType *input)
virtual void	PushFrontInput (const InputImageType *input)
virtual void	SetInput (const DataObjectIdentifierType &key, DataObject *input)
virtual void	SetInput (const InputImageType *input)
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 > >
OutputImageType *	GetOutput (unsigned int idx)
OutputImageType *	GetOutput ()
const OutputImageType *	GetOutput () const
virtual void	GraftOutput (DataObject *graft)
virtual void	GraftOutput (const DataObjectIdentifierType &key, DataObject *graft)
virtual void	GraftNthOutput (unsigned int idx, DataObject *graft)
ProcessObject::DataObjectPointer	MakeOutput (ProcessObject::DataObjectPointerArraySizeType idx) override
ProcessObject::DataObjectPointer	MakeOutput (const ProcessObject::DataObjectIdentifierType &) override
Public Member Functions inherited from itk::ProcessObject
virtual void	AbortGenerateDataOn ()
virtual void	EnlargeOutputRequestedRegion (DataObject *)
virtual const bool &	GetAbortGenerateData () const
DataObjectPointerArray	GetIndexedInputs ()
DataObjectPointerArray	GetIndexedOutputs ()
NameArray	GetInputNames () const
DataObjectPointerArray	GetInputs ()
MultiThreaderType *	GetMultiThreader () const
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	PrepareOutputs ()
virtual void	PropagateRequestedRegion (DataObject *output)
virtual void	ResetPipeline ()
virtual void	SetAbortGenerateData (bool _arg)
void	SetMultiThreader (MultiThreaderType *threader)
virtual void	Update ()
virtual void	UpdateLargestPossibleRegion ()
virtual void	UpdateOutputData (DataObject *output)
virtual void	UpdateOutputInformation ()
void	UpdateProgress (float progress)
virtual void	SetReleaseDataFlag (bool val)
virtual bool	GetReleaseDataFlag () const
void	ReleaseDataFlagOn ()
void	ReleaseDataFlagOff ()
virtual void	SetReleaseDataBeforeUpdateFlag (bool _arg)
virtual const bool &	GetReleaseDataBeforeUpdateFlag () const
virtual void	ReleaseDataBeforeUpdateFlagOn ()
virtual void	SetNumberOfWorkUnits (ThreadIdType _arg)
virtual const ThreadIdType &	GetNumberOfWorkUnits () const
Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *)
unsigned long	AddObserver (const EventObject &event, Command *) const
unsigned long	AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const
LightObject::Pointer	CreateAnother () const override
virtual void	DebugOff () const
virtual void	DebugOn () const
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
MetaDataDictionary &	GetMetaDataDictionary ()
const MetaDataDictionary &	GetMetaDataDictionary () const
virtual ModifiedTimeType	GetMTime () const
virtual const TimeStamp &	GetTimeStamp () 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
Pointer	Clone () const
virtual void	Delete ()
virtual int	GetReferenceCount () const
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 double	GetGlobalDefaultCoordinateTolerance ()
static double	GetGlobalDefaultDirectionTolerance ()
static void	SetGlobalDefaultCoordinateTolerance (double)
static void	SetGlobalDefaultDirectionTolerance (double)
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 ()

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

Protected Member Functions
	BayesianClassifierImageFilter ()
virtual void	ClassifyBasedOnPosteriors ()
virtual void	ComputeBayesRule ()
void	GenerateData () override
void	GenerateOutputInformation () override
PosteriorsImageType *	GetPosteriorImage ()
virtual void	NormalizeAndSmoothPosteriors ()
void	PrintSelf (std::ostream &os, Indent indent) const override
	~BayesianClassifierImageFilter () override=default
Protected Member Functions inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > >
virtual void	CallCopyInputRegionToOutputRegion (OutputImageRegionType &destRegion, const InputImageRegionType &srcRegion)
virtual void	CallCopyOutputRegionToInputRegion (InputImageRegionType &destRegion, const OutputImageRegionType &srcRegion)
void	GenerateInputRequestedRegion () override
	ImageToImageFilter ()
void	PrintSelf (std::ostream &os, Indent indent) const override
void	VerifyInputInformation () ITKv5_CONST override
	~ImageToImageFilter () override=default
virtual void	PushBackInput (const DataObject *input)
virtual void	PushFrontInput (const DataObject *input)
Protected Member Functions inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage::ImageDimension > >
virtual void	AfterThreadedGenerateData ()
virtual void	AllocateOutputs ()
virtual void	BeforeThreadedGenerateData ()
void	ClassicMultiThread (ThreadFunctionType callbackFunction)
void	GenerateData () override
virtual const ImageRegionSplitterBase *	GetImageRegionSplitter () const
	ImageSource ()
virtual unsigned int	SplitRequestedRegion (unsigned int i, unsigned int pieces, OutputImageRegionType &splitRegion)
	~ImageSource () override=default
virtual void	ThreadedGenerateData (const OutputImageRegionType &region, ThreadIdType threadId)
virtual void	DynamicThreadedGenerateData (const OutputImageRegionType &outputRegionForThread)
virtual bool	GetDynamicMultiThreading () const
virtual void	SetDynamicMultiThreading (bool _arg)
virtual void	DynamicMultiThreadingOn ()
Protected Member Functions inherited from itk::ProcessObject
virtual void	AddInput (DataObject *input)
void	AddOptionalInputName (const DataObjectIdentifierType &)
void	AddOptionalInputName (const DataObjectIdentifierType &, DataObjectPointerArraySizeType idx)
virtual void	AddOutput (DataObject *output)
bool	AddRequiredInputName (const DataObjectIdentifierType &)
bool	AddRequiredInputName (const DataObjectIdentifierType &, DataObjectPointerArraySizeType idx)
virtual void	CacheInputReleaseDataFlags ()
virtual void	GenerateOutputRequestedRegion (DataObject *output)
DataObject *	GetInput (const DataObjectIdentifierType &key)
const DataObject *	GetInput (const DataObjectIdentifierType &key) const
virtual const DataObjectPointerArraySizeType &	GetNumberOfRequiredInputs () const
virtual const DataObjectPointerArraySizeType &	GetNumberOfRequiredOutputs () const
bool	IsIndexedInputName (const DataObjectIdentifierType &) const
bool	IsIndexedOutputName (const DataObjectIdentifierType &) const
bool	IsRequiredInputName (const DataObjectIdentifierType &) const
DataObjectPointerArraySizeType	MakeIndexFromInputName (const DataObjectIdentifierType &name) const
DataObjectPointerArraySizeType	MakeIndexFromOutputName (const DataObjectIdentifierType &name) const
DataObjectIdentifierType	MakeNameFromInputIndex (DataObjectPointerArraySizeType idx) const
DataObjectIdentifierType	MakeNameFromOutputIndex (DataObjectPointerArraySizeType idx) const
	ProcessObject ()
virtual void	PropagateResetPipeline ()
virtual void	PushBackInput (const DataObject *input)
virtual void	PushFrontInput (const DataObject *input)
virtual void	ReleaseInputs ()
virtual void	RemoveInput (const DataObjectIdentifierType &key)
virtual void	RemoveInput (DataObjectPointerArraySizeType)
virtual void	RemoveOutput (const DataObjectIdentifierType &key)
virtual void	RemoveOutput (DataObjectPointerArraySizeType idx)
bool	RemoveRequiredInputName (const DataObjectIdentifierType &)
virtual void	RestoreInputReleaseDataFlags ()
virtual void	SetInput (const DataObjectIdentifierType &key, DataObject *input)
virtual void	SetNthInput (DataObjectPointerArraySizeType idx, DataObject *input)
virtual void	SetNthOutput (DataObjectPointerArraySizeType idx, DataObject *output)
void	SetNumberOfIndexedInputs (DataObjectPointerArraySizeType num)
void	SetNumberOfIndexedOutputs (DataObjectPointerArraySizeType num)
virtual void	SetNumberOfRequiredInputs (DataObjectPointerArraySizeType)
virtual void	SetNumberOfRequiredOutputs (DataObjectPointerArraySizeType _arg)
virtual void	SetOutput (const DataObjectIdentifierType &name, DataObject *output)
virtual void	SetPrimaryInput (DataObject *object)
virtual void	SetPrimaryOutput (DataObject *object)
void	SetRequiredInputNames (const NameArray &)
virtual void	VerifyPreconditions () ITKv5_CONST
	~ProcessObject () override
DataObject *	GetInput (DataObjectPointerArraySizeType idx)
const DataObject *	GetInput (DataObjectPointerArraySizeType idx) const
DataObject *	GetPrimaryInput ()
const DataObject *	GetPrimaryInput () const
virtual void	SetPrimaryInputName (const DataObjectIdentifierType &key)
virtual const char *	GetPrimaryInputName () const
DataObject *	GetOutput (const DataObjectIdentifierType &key)
const DataObject *	GetOutput (const DataObjectIdentifierType &key) const
virtual void	SetPrimaryOutputName (const DataObjectIdentifierType &key)
virtual const char *	GetPrimaryOutputName () const
DataObject *	GetOutput (DataObjectPointerArraySizeType i)
const DataObject *	GetOutput (DataObjectPointerArraySizeType i) const
DataObject *	GetPrimaryOutput ()
const DataObject *	GetPrimaryOutput () const
virtual bool	GetThreaderUpdateProgress () const
virtual void	ThreaderUpdateProgressOn ()
virtual void	SetThreaderUpdateProgress (bool arg)
Protected Member Functions inherited from itk::Object
	Object ()
bool	PrintObservers (std::ostream &os, Indent indent) const
virtual void	SetTimeStamp (const TimeStamp &timeStamp)
	~Object () override
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 ()

Private Attributes
unsigned int	m_NumberOfSmoothingIterations { 0 }
SmoothingFilterPointer	m_SmoothingFilter {}
bool	m_UserProvidedPriors { false }
bool	m_UserProvidedSmoothingFilter { false }

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 >
Static Protected Member Functions inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage::ImageDimension > >
static const ImageRegionSplitterBase *	GetGlobalDefaultSplitter ()
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
TimeStamp	m_OutputInformationMTime {}
bool	m_Updating {}
Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount {}

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.

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.

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

~BayesianClassifierImageFilter()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>

itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::~BayesianClassifierImageFilter ( )

overrideprotecteddefault

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.

GenerateData()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>

void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GenerateData ( )

overrideprotectedvirtual

This method causes the filter to generate its output.

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

Generate the information describing the output data. The default implementation of this method will copy information from the input to the output. A filter may override this method if its output will have different information than its input. For instance, a filter that shrinks an image will need to provide an implementation for this method that changes the spacing of the pixels. Such filters should call their superclass' implementation of this method prior to changing the information values they need (i.e. GenerateOutputInformation() should call Superclass::GenerateOutputInformation() prior to changing the information.

Reimplemented from itk::ProcessObject.

GetNameOfClass()

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>

const char* itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GetNameOfClass ( ) const

overridevirtual

See also

LightObject::GetNameOfClass()

Reimplemented from itk::ProcessObject.

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

Number of iterations to apply the smoothing filter.

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

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

Make a DataObject of the correct type to used as the specified output.

Every ProcessObject subclass must be able to create a DataObject that can be used as a specified output. This method is automatically called when DataObject::DisconnectPipeline() is called. DataObject::DisconnectPipeline, disconnects a data object from being an output of its current source. When the data object is disconnected, the ProcessObject needs to construct a replacement output data object so that the ProcessObject is in a valid state. So DataObject::DisconnectPipeline eventually calls ProcessObject::MakeOutput. Note that MakeOutput always returns a itkSmartPointer to a DataObject. ImageSource and MeshSource override this method to create the correct type of image and mesh respectively. If a filter has multiple outputs of different types, then that filter must provide an implementation of MakeOutput().

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

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

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

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

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

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

Definition at line 231 of file itkBayesianClassifierImageFilter.h.

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

• itkBayesianClassifierImageFilter.h