ITK  6.0.0
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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 InputImageTypeGetInput () const
 
const InputImageTypeGetInput (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 > >
OutputImageTypeGetOutput (unsigned int idx)
 
OutputImageTypeGetOutput ()
 
const OutputImageTypeGetOutput () 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 ()
 
MultiThreaderTypeGetMultiThreader () 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 ThreadIdTypeGetNumberOfWorkUnits () const
 
- Public Member Functions inherited from itk::Object
unsigned long AddObserver (const EventObject &event, Command *cmd) 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
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary ()
 
const MetaDataDictionaryGetMetaDataDictionary () const
 
virtual ModifiedTimeType GetMTime () const
 
virtual const TimeStampGetTimeStamp () const
 
bool HasObserver (const EventObject &event) const
 
void InvokeEvent (const EventObject &)
 
void InvokeEvent (const EventObject &) const
 
virtual void Modified () const
 
void Register () const override
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag) const
 
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
 
PosteriorsImageTypeGetPosteriorImage ()
 
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 () 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 ImageRegionSplitterBaseGetImageRegionSplitter () 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)
 
DataObjectGetInput (const DataObjectIdentifierType &key)
 
const DataObjectGetInput (const DataObjectIdentifierType &key) const
 
virtual const DataObjectPointerArraySizeTypeGetNumberOfRequiredInputs () const
 
virtual const DataObjectPointerArraySizeTypeGetNumberOfRequiredOutputs () 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 () const
 
 ~ProcessObject () override
 
DataObjectGetInput (DataObjectPointerArraySizeType idx)
 
const DataObjectGetInput (DataObjectPointerArraySizeType idx) const
 
DataObjectGetPrimaryInput ()
 
const DataObjectGetPrimaryInput () const
 
virtual void SetPrimaryInputName (const DataObjectIdentifierType &key)
 
virtual const char * GetPrimaryInputName () const
 
DataObjectGetOutput (const DataObjectIdentifierType &key)
 
const DataObjectGetOutput (const DataObjectIdentifierType &key) const
 
virtual void SetPrimaryOutputName (const DataObjectIdentifierType &key)
 
virtual const char * GetPrimaryOutputName () const
 
DataObjectGetOutput (DataObjectPointerArraySizeType i)
 
const DataObjectGetOutput (DataObjectPointerArraySizeType i) const
 
DataObjectGetPrimaryOutput ()
 
const DataObjectGetPrimaryOutput () 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 ImageRegionSplitterBaseGetGlobalDefaultSplitter ()
 
static ITK_THREAD_RETURN_FUNCTION_CALL_CONVENTION ThreaderCallback (void *arg)
 
- Static Protected Member Functions inherited from itk::ProcessObject
template<typename TSourceObject >
static void MakeRequiredOutputs (TSourceObject &sourceObject, const DataObjectPointerArraySizeType numberOfRequiredOutputs)
 
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

◆ 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.


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