ITK  4.6.0
Insight Segmentation and Registration Toolkit
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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 >:

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:
Statistics/BayesianClassifier.cxx.

Definition at line 81 of file itkBayesianClassifierImageFilter.h.

Public Types

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

Public Member Functions

virtual ::itk::LightObject::Pointer CreateAnother (void) const
 
virtual const char * GetNameOfClass () const
 
virtual SmoothingFilterPointer GetSmoothingFilter () const
 
virtual DataObjectPointer MakeOutput (DataObjectPointerArraySizeType idx)
 
virtual void SetPriors (const PriorsImageType *)
 
void SetSmoothingFilter (SmoothingFilterType *)
 
 typedef (Concept::Convertible< unsigned int, TLabelsType >) UnsignedIntConvertibleToLabelsCheck
 
 typedef (Concept::AdditiveOperators< TPosteriorsPrecisionType >) PosteriorsAdditiveOperatorsCheck
 
 typedef (Concept::Convertible< int, TPosteriorsPrecisionType >) IntConvertibleToPosteriorsCheck
 
 typedef (Concept::HasNumericTraits< typename InputPixelType::ValueType >) InputHasNumericTraitsCheck
 
 typedef (Concept::HasNumericTraits< TPosteriorsPrecisionType >) PosteriorsHasNumericTraitsCheck
 
 typedef (Concept::HasNumericTraits< TPriorsPrecisionType >) PriorsHasNumericTraitsCheck
 
 typedef (Concept::MultiplyOperator< typename InputPixelType::ValueType, PriorsPixelType, PosteriorsPixelType >) InputPriorsPosteriorsMultiplyOperatorCheck
 
virtual void SetNumberOfSmoothingIterations (unsigned int _arg)
 
virtual unsigned int GetNumberOfSmoothingIterations () const
 
- Public Member Functions inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > >
const InputImageTypeGetInput (void) const
 
const InputImageTypeGetInput (unsigned int idx) const
 
virtual void PopBackInput ()
 
virtual void PopFrontInput ()
 
virtual void PushBackInput (const InputImageType *image)
 
virtual void PushFrontInput (const InputImageType *image)
 
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 (unsigned int idx)
 
virtual void GraftNthOutput (unsigned int idx, DataObject *output)
 
virtual void GraftOutput (DataObject *output)
 
virtual void GraftOutput (const DataObjectIdentifierType &key, DataObject *output)
 
OutputImageTypeGetOutput (void)
 
const OutputImageTypeGetOutput (void) const
 
- Public Member Functions inherited from itk::ProcessObject
virtual void AbortGenerateDataOff ()
 
virtual void AbortGenerateDataOn ()
 
virtual void EnlargeOutputRequestedRegion (DataObject *)
 
virtual const bool & GetAbortGenerateData () const
 
NameArray GetInputNames () const
 
MultiThreader * GetMultiThreader () const
 
DataObjectPointerArraySizeType GetNumberOfIndexedInputs () const
 
DataObjectPointerArraySizeType GetNumberOfInputs () const
 
DataObjectPointerArraySizeType GetNumberOfOutputs () const
 
virtual
DataObjectPointerArraySizeType 
GetNumberOfValidRequiredInputs () const
 
NameArray GetOutputNames () const
 
virtual const float & GetProgress () const
 
NameArray GetRequiredInputNames () const
 
bool HasInput (const DataObjectIdentifierType &key) const
 
bool HasOutput (const DataObjectIdentifierType &key) const
 
virtual DataObjectPointer MakeOutput (const DataObjectIdentifierType &)
 
virtual void PrepareOutputs ()
 
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)
 
DataObjectPointerArray GetInputs ()
 
DataObjectPointerArray GetOutputs ()
 
DataObjectPointerArray GetIndexedInputs ()
 
DataObjectPointerArray GetIndexedOutputs ()
 
DataObjectPointerArraySizeType GetNumberOfIndexedOutputs () const
 
void SetProgress (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 SetNumberOfThreads (ThreadIdType _arg)
 
virtual const ThreadIdTypeGetNumberOfThreads () const
 
- 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 (void)
 
const MetaDataDictionaryGetMetaDataDictionary (void) 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
 
virtual void Register () const ITK_OVERRIDE
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
void SetDebug (bool debugFlag) const
 
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
 
virtual void SetReferenceCount (int) ITK_OVERRIDE
 
virtual void UnRegister () const ITK_OVERRIDE
 
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::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 const unsigned int Dimension = InputImageType ::ImageDimension
 
- Static Public Attributes inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > >
static const unsigned int InputImageDimension
 
static const unsigned int OutputImageDimension
 
- Static Public Attributes inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage::ImageDimension > >
static const unsigned int OutputImageDimension
 

Protected Member Functions

 BayesianClassifierImageFilter ()
 
virtual void ClassifyBasedOnPosteriors ()
 
virtual void ComputeBayesRule ()
 
virtual void GenerateData ()
 
virtual void GenerateOutputInformation (void)
 
PosteriorsImageTypeGetPosteriorImage ()
 
virtual void NormalizeAndSmoothPosteriors ()
 
void PrintSelf (std::ostream &os, Indent indent) const
 
virtual ~BayesianClassifierImageFilter ()
 
- 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)
 
virtual void GenerateInputRequestedRegion ()
 
 ImageToImageFilter ()
 
virtual void VerifyInputInformation ()
 
 ~ImageToImageFilter ()
 
void PushBackInput (const DataObject *input)
 
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 ()
 
virtual const
ImageRegionSplitterBase
GetImageRegionSplitter (void) const
 
 ImageSource ()
 
virtual unsigned int SplitRequestedRegion (unsigned int i, unsigned int pieces, OutputImageRegionType &splitRegion)
 
virtual void ThreadedGenerateData (const OutputImageRegionType &outputRegionForThread, ThreadIdType threadId)
 
virtual ~ImageSource ()
 
- Protected Member Functions inherited from itk::ProcessObject
virtual void AddInput (DataObject *input)
 
virtual void AddOutput (DataObject *output)
 
virtual void CacheInputReleaseDataFlags ()
 
virtual void GenerateOutputRequestedRegion (DataObject *output)
 
virtual const
DataObjectPointerArraySizeType
GetNumberOfRequiredOutputs () const
 
bool IsIndexedInputName (const DataObjectIdentifierType &) const
 
bool IsIndexedOutputName (const DataObjectIdentifierType &) const
 
 itkLegacyMacro (virtual void RemoveOutput(DataObject *output))
 
 itkLegacyMacro (void SetNumberOfOutputs(DataObjectPointerArraySizeType num))
 
 itkLegacyMacro (virtual void RemoveInput(DataObject *input))
 
 itkLegacyMacro (void SetNumberOfInputs(DataObjectPointerArraySizeType num))
 
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 ReleaseInputs ()
 
virtual void RemoveInput (const DataObjectIdentifierType &key)
 
virtual void RemoveInput (DataObjectPointerArraySizeType)
 
virtual void RemoveOutput (const DataObjectIdentifierType &key)
 
virtual void RemoveOutput (DataObjectPointerArraySizeType idx)
 
virtual void RestoreInputReleaseDataFlags ()
 
virtual void SetInput (const DataObjectIdentifierType &key, DataObject *input)
 
virtual void SetNthInput (DataObjectPointerArraySizeType num, DataObject *input)
 
virtual void SetNthOutput (DataObjectPointerArraySizeType num, DataObject *output)
 
void SetNumberOfIndexedInputs (DataObjectPointerArraySizeType num)
 
void SetNumberOfIndexedOutputs (DataObjectPointerArraySizeType num)
 
virtual void SetNumberOfRequiredOutputs (DataObjectPointerArraySizeType _arg)
 
virtual void SetOutput (const DataObjectIdentifierType &key, DataObject *output)
 
virtual void SetPrimaryInput (DataObject *input)
 
virtual void SetPrimaryOutput (DataObject *output)
 
virtual void VerifyPreconditions ()
 
 ~ProcessObject ()
 
DataObjectGetInput (const DataObjectIdentifierType &key)
 
const DataObjectGetInput (const DataObjectIdentifierType &key) const
 
DataObjectGetInput (DataObjectPointerArraySizeType idx)
 
const DataObjectGetInput (DataObjectPointerArraySizeType idx) const
 
DataObjectGetPrimaryInput ()
 
const DataObjectGetPrimaryInput () const
 
virtual void SetPrimaryInputName (const DataObjectIdentifierType &key)
 
virtual const char * GetPrimaryInputName (void) const
 
virtual void SetNumberOfRequiredInputs (DataObjectPointerArraySizeType)
 
virtual const
DataObjectPointerArraySizeType
GetNumberOfRequiredInputs () const
 
bool AddRequiredInputName (const DataObjectIdentifierType &)
 
bool AddRequiredInputName (const DataObjectIdentifierType &, DataObjectPointerArraySizeType idx)
 
bool RemoveRequiredInputName (const DataObjectIdentifierType &)
 
bool IsRequiredInputName (const DataObjectIdentifierType &) const
 
void SetRequiredInputNames (const NameArray &)
 
DataObjectGetOutput (const DataObjectIdentifierType &key)
 
const DataObjectGetOutput (const DataObjectIdentifierType &key) const
 
virtual void SetPrimaryOutputName (const DataObjectIdentifierType &key)
 
virtual const char * GetPrimaryOutputName (void) const
 
DataObjectGetOutput (DataObjectPointerArraySizeType idx)
 
const DataObjectGetOutput (DataObjectPointerArraySizeType idx) const
 
DataObjectGetPrimaryOutput ()
 
const DataObjectGetPrimaryOutput () const
 
- Protected Member Functions inherited from itk::Object
 Object ()
 
bool PrintObservers (std::ostream &os, Indent indent) const
 
virtual void SetTimeStamp (const TimeStamp &time)
 
virtual ~Object ()
 
- 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 Member Functions

 BayesianClassifierImageFilter (const Self &)
 
void operator= (const Self &)
 

Private Attributes

unsigned int m_NumberOfSmoothingIterations
 
SmoothingFilterPointer m_SmoothingFilter
 
bool m_UserProvidedPriors
 
bool m_UserProvidedSmoothingFilter
 

Additional Inherited Members

- Protected Types inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > >
typedef
ImageToImageFilterDetail::ImageRegionCopier
< itkGetStaticConstMacro(OutputImageDimension),
itkGetStaticConstMacro(InputImageDimension) > 
InputToOutputRegionCopierType
 
typedef
ImageToImageFilterDetail::ImageRegionCopier
< itkGetStaticConstMacro(InputImageDimension),
itkGetStaticConstMacro(OutputImageDimension) > 
OutputToInputRegionCopierType
 
- Protected Types inherited from itk::LightObject
typedef int InternalReferenceCountType
 
- Static Protected Member Functions inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage::ImageDimension > >
static const
ImageRegionSplitterBase
GetGlobalDefaultSplitter ()
 
static ITK_THREAD_RETURN_TYPE ThreaderCallback (void *arg)
 
- Protected Attributes inherited from itk::ProcessObject
TimeStamp m_OutputInformationMTime
 
bool m_Updating
 
- Protected Attributes inherited from itk::LightObject
InternalReferenceCountType m_ReferenceCount
 
SimpleFastMutexLock m_ReferenceCountLock
 

Member Typedef Documentation

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

Definition at line 94 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 155 of file itkBayesianClassifierImageFilter.h.

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

This is overloaded to create the Posteriors output image

Definition at line 179 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 153 of file itkBayesianClassifierImageFilter.h.

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

Decision rule to use for defining the label

Definition at line 152 of file itkBayesianClassifierImageFilter.h.

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
typedef itk::Image< TPosteriorsPrecisionType, itkGetStaticConstMacro(Dimension) > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::ExtractedComponentImageType

An image from a single component of the Posterior

Definition at line 159 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 113 of file itkBayesianClassifierImageFilter.h.

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

Input and Output image iterators

Definition at line 116 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 111 of file itkBayesianClassifierImageFilter.h.

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

Input and Output image types

Definition at line 100 of file itkBayesianClassifierImageFilter.h.

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

Pixel types.

Definition at line 120 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 139 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 138 of file itkBayesianClassifierImageFilter.h.

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

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 136 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 137 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 117 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 112 of file itkBayesianClassifierImageFilter.h.

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
typedef Image< TLabelsType, itkGetStaticConstMacro(Dimension) > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::OutputImageType

Definition at line 110 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 121 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 93 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 149 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 148 of file itkBayesianClassifierImageFilter.h.

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
typedef VectorImage< TPosteriorsPrecisionType, itkGetStaticConstMacro(Dimension) > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PosteriorsImageType

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 146 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 147 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 131 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 130 of file itkBayesianClassifierImageFilter.h.

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
typedef VectorImage< TPriorsPrecisionType, itkGetStaticConstMacro(Dimension) > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PriorsImageType

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 128 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 129 of file itkBayesianClassifierImageFilter.h.

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

Standard class typedefs.

Definition at line 88 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 166 of file itkBayesianClassifierImageFilter.h.

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

Optional Smoothing filter that will be applied to the Posteriors

Definition at line 164 of file itkBayesianClassifierImageFilter.h.

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

Definition at line 91 of file itkBayesianClassifierImageFilter.h.

Constructor & Destructor Documentation

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

Definition at line 210 of file itkBayesianClassifierImageFilter.h.

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

Member Function Documentation

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

Methods for computing the labeled map for all combinations of conditions

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

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

Here is where the classification is computed.

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

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

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.

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 > >.

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

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
PosteriorsImageType* itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GetPosteriorImage ( )
protected
template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual SmoothingFilterPointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::GetSmoothingFilter ( ) const
virtual
template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
virtual DataObjectPointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MakeOutput ( DataObjectPointerArraySizeType  idx)
virtual

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::ImageSource< Image< TLabelsType, TInputVectorImage::ImageDimension > >.

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.

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

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::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > >.

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

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

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

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

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::typedef ( Concept::Convertible< unsigned int, TLabelsType >  )

This class requires UnsignedIntConvertibleToLabelsCheck in the form of ( Concept::Convertible< unsigned int, TLabelsType > )

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

This class requires PosteriorsAdditiveOperatorsCheck in the form of ( Concept::AdditiveOperators< TPosteriorsPrecisionType > )

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::typedef ( Concept::Convertible< int, TPosteriorsPrecisionType >  )

This class requires IntConvertibleToPosteriorsCheck in the form of ( Concept::Convertible< int, TPosteriorsPrecisionType > )

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::typedef ( Concept::HasNumericTraits< typename InputPixelType::ValueType >  )

This class requires InputHasNumericTraitsCheck in the form of ( Concept::HasNumericTraits< typename InputPixelType::ValueType > )

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

This class requires PosteriorsHasNumericTraitsCheck in the form of ( Concept::HasNumericTraits< TPosteriorsPrecisionType > )

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

This class requires PriorsHasNumericTraitsCheck in the form of ( Concept::HasNumericTraits< TPriorsPrecisionType > )

template<typename TInputVectorImage , typename TLabelsType = unsigned char, typename TPosteriorsPrecisionType = double, typename TPriorsPrecisionType = double>
itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::typedef ( Concept::MultiplyOperator< typename InputPixelType::ValueType, PriorsPixelType, PosteriorsPixelType )

This class requires InputPriorsPosteriorsMultiplyOperatorCheck in the form of ( Concept::MultiplyOperator< typename InputPixelType::ValueType, PriorsPixelType, PosteriorsPixelType > )

Member Data Documentation

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

Dimension of the input image

Definition at line 107 of file itkBayesianClassifierImageFilter.h.

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

Number of iterations to apply the smoothing filter

Definition at line 243 of file itkBayesianClassifierImageFilter.h.

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

Pointer to optional Smoothing filter

Definition at line 240 of file itkBayesianClassifierImageFilter.h.

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

Boolean flag indicating that the user defined the Priors optional input

Definition at line 234 of file itkBayesianClassifierImageFilter.h.

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

Boolean flag indicating that the user provided a Smoothing filter

Definition at line 237 of file itkBayesianClassifierImageFilter.h.


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