ITK  5.4.0
Insight Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Private Types | Private Member Functions | Private Attributes | Static Private Attributes | List of all members
itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage > Class Template Reference

#include <itkImageGaussianModelEstimator.h>

Detailed Description

template<typename TInputImage, typename TMembershipFunction, typename TTrainingImage>
class itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >

Base class for ImageGaussianModelEstimator object.

itkImageGaussianModelEstimator generates the Gaussian model for given tissue types (or class types) in an input training data set for segmentation. The training data set is typically provided as a set of labelled/classified data set by the user. A Gaussian model is generated for each label present in the training data set.

The user should ensure that both the input and training images are of the same size. The input data consists of the raw data and the training data has class labels associated with each pixel.

A zero label is used to identify the background. A model is not calculated for the background (its mean and covariance will be zero). Positive labels are classes for which models will be estimated. Negative labels indicate unlabeled data where no models will be estimated.

This object supports data handling of multiband images. The object accepts the input image in vector format only, where each pixel is a vector and each element of the vector corresponds to an entry from 1 particular band of a multiband dataset. A single band image is treated as a vector image with a single element for every vector. The classified image is treated as a single band scalar image.

This function is templated over the type of input and output images. In addition, a third parameter for the MembershipFunction needs to be specified. In this case a Membership function that stores Gaussian models needs to be specified.

The function EstimateModels() calculates the various models, creates the membership function objects and populates them.

Examples
Examples/Segmentation/GibbsPriorImageFilter1.cxx.

Definition at line 77 of file itkImageGaussianModelEstimator.h.

+ Inheritance diagram for itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >:
+ Collaboration diagram for itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >:

Public Types

using ConstPointer = SmartPointer< const Self >
 
using InputImageConstIterator = ImageRegionConstIterator< TInputImage >
 
using InputImageConstPointer = typename TInputImage::ConstPointer
 
using InputImageIterator = ImageRegionIterator< TInputImage >
 
using InputImagePixelType = typename TInputImage::PixelType
 
using InputImagePointer = typename TInputImage::Pointer
 
using InputImageType = TInputImage
 
using MembershipFunctionPointer = typename TMembershipFunction::Pointer
 
using MembershipFunctionType = TMembershipFunction
 
using Pointer = SmartPointer< Self >
 
using Self = ImageGaussianModelEstimator
 
using Superclass = ImageModelEstimatorBase< TInputImage, TMembershipFunction >
 
using TrainingImageConstIterator = ImageRegionConstIterator< TTrainingImage >
 
using TrainingImageConstPointer = typename TTrainingImage::ConstPointer
 
using TrainingImageIterator = ImageRegionIterator< TTrainingImage >
 
using TrainingImagePixelType = typename TTrainingImage::PixelType
 
using TrainingImagePointer = typename TTrainingImage::Pointer
 
using TrainingImageType = TTrainingImage
 
- Public Types inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
using ConstPointer = SmartPointer< const Self >
 
using InputImagePointer = typename TInputImage::Pointer
 
using InputImageType = TInputImage
 
using MembershipFunctionPointer = typename TMembershipFunction::Pointer
 
using MembershipFunctionPointerVector = std::vector< MembershipFunctionPointer >
 
using Pointer = SmartPointer< Self >
 
using Self = ImageModelEstimatorBase
 
using Superclass = LightProcessObject
 
- Public Types inherited from itk::LightProcessObject
using ConstPointer = SmartPointer< const Self >
 
using Pointer = SmartPointer< Self >
 
using Self = LightProcessObject
 
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

 itkOverrideGetNameOfClassMacro (ImageGaussianModelEstimator)
 
virtual void SetTrainingImage (TrainingImageType *_arg)
 
virtual TrainingImageTypeGetModifiableTrainingImage ()
 
- Public Member Functions inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
unsigned int AddMembershipFunction (MembershipFunctionPointer function)
 
void DeleteAllMembershipFunctions ()
 
const MembershipFunctionPointerVector GetMembershipFunctions () const
 
unsigned int GetNumberOfMembershipFunctions ()
 
virtual const unsigned int & GetNumberOfModels () const
 
 itkOverrideGetNameOfClassMacro (ImageModelEstimatorBase)
 
void SetMembershipFunctions (MembershipFunctionPointerVector membershipFunctions)
 
virtual void SetNumberOfModels (unsigned int _arg)
 
void Update ()
 
virtual void SetInputImage (InputImageType *_arg)
 
virtual InputImageTypeGetModifiableInputImage ()
 
- Public Member Functions inherited from itk::LightProcessObject
virtual void AbortGenerateDataOn ()
 
virtual const bool & GetAbortGenerateData () const
 
 itkOverrideGetNameOfClassMacro (LightProcessObject)
 
virtual void SetAbortGenerateData (bool _arg)
 
virtual void UpdateOutputData ()
 
void UpdateProgress (float amount)
 
virtual void SetProgress (float _arg)
 
virtual const float & GetProgress () const
 
- Public Member Functions inherited from itk::Object
unsigned long AddObserver (const EventObject &event, Command *)
 
unsigned long AddObserver (const EventObject &event, Command *) const
 
unsigned long AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const
 
LightObject::Pointer CreateAnother () const override
 
virtual void DebugOff () const
 
virtual void DebugOn () const
 
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
 
 itkOverrideGetNameOfClassMacro (Object)
 
virtual void Modified () const
 
void Register () const override
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
void SetDebug (bool debugFlag) const
 
void SetReferenceCount (int) override
 
void UnRegister () const noexcept override
 
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
 
void SetMetaDataDictionary (MetaDataDictionary &&rrhs)
 
virtual void SetObjectName (std::string _arg)
 
virtual const std::string & GetObjectName () const
 
- Public Member Functions inherited from itk::LightObject
Pointer Clone () const
 
virtual void Delete ()
 
virtual int GetReferenceCount () const
 
 itkVirtualGetNameOfClassMacro (LightObject)
 
void Print (std::ostream &os, Indent indent=0) const
 

Static Public Member Functions

static Pointer New ()
 
- Static Public Member Functions inherited from itk::LightProcessObject
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 val)
 
- Static Public Member Functions inherited from itk::LightObject
static void BreakOnError ()
 
static Pointer New ()
 

Protected Member Functions

void GenerateData () override
 
 ImageGaussianModelEstimator ()=default
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
 ~ImageGaussianModelEstimator () override=default
 
- Protected Member Functions inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
void GenerateData () override
 
 ImageModelEstimatorBase ()
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
 ~ImageModelEstimatorBase () override=default
 
- Protected Member Functions inherited from itk::LightProcessObject
 LightProcessObject ()
 
 ~LightProcessObject () override
 
- 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 Types

using InputImageSizeType = typename TInputImage::SizeType
 
using MatrixType = vnl_matrix< double >
 

Private Member Functions

void EstimateGaussianModelParameters ()
 
void EstimateModels () override
 

Private Attributes

std::unique_ptr< MatrixType[]> m_Covariance { nullptr }
 
MatrixType m_Means {}
 
MatrixType m_NumberOfSamples {}
 
TrainingImagePointer m_TrainingImage {}
 

Static Private Attributes

static constexpr unsigned int VectorDimension = InputImagePixelType::Dimension
 

Additional Inherited Members

- Protected Attributes inherited from itk::LightObject
std::atomic< int > m_ReferenceCount {}
 

Member Typedef Documentation

◆ ConstPointer

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::ConstPointer = SmartPointer<const Self>

Definition at line 86 of file itkImageGaussianModelEstimator.h.

◆ InputImageConstIterator

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::InputImageConstIterator = ImageRegionConstIterator<TInputImage>

Definition at line 114 of file itkImageGaussianModelEstimator.h.

◆ InputImageConstPointer

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::InputImageConstPointer = typename TInputImage::ConstPointer

Definition at line 97 of file itkImageGaussianModelEstimator.h.

◆ InputImageIterator

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::InputImageIterator = ImageRegionIterator<TInputImage>

Type definitions for the iterators for the input and training images.

Definition at line 113 of file itkImageGaussianModelEstimator.h.

◆ InputImagePixelType

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::InputImagePixelType = typename TInputImage::PixelType

Type definition for the vector associated with input image pixel type.

Definition at line 106 of file itkImageGaussianModelEstimator.h.

◆ InputImagePointer

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::InputImagePointer = typename TInputImage::Pointer

Definition at line 96 of file itkImageGaussianModelEstimator.h.

◆ InputImageSizeType

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::InputImageSizeType = typename TInputImage::SizeType
private

Definition at line 140 of file itkImageGaussianModelEstimator.h.

◆ InputImageType

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::InputImageType = TInputImage

Type definition for the input image.

Definition at line 95 of file itkImageGaussianModelEstimator.h.

◆ MatrixType

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::MatrixType = vnl_matrix<double>
private

Definition at line 138 of file itkImageGaussianModelEstimator.h.

◆ MembershipFunctionPointer

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::MembershipFunctionPointer = typename TMembershipFunction::Pointer

Definition at line 120 of file itkImageGaussianModelEstimator.h.

◆ MembershipFunctionType

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::MembershipFunctionType = TMembershipFunction

Type definitions for the membership function .

Definition at line 119 of file itkImageGaussianModelEstimator.h.

◆ Pointer

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::Pointer = SmartPointer<Self>

Definition at line 85 of file itkImageGaussianModelEstimator.h.

◆ Self

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::Self = ImageGaussianModelEstimator

Standard class type aliases.

Definition at line 83 of file itkImageGaussianModelEstimator.h.

◆ Superclass

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::Superclass = ImageModelEstimatorBase<TInputImage, TMembershipFunction>

Definition at line 84 of file itkImageGaussianModelEstimator.h.

◆ TrainingImageConstIterator

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::TrainingImageConstIterator = ImageRegionConstIterator<TTrainingImage>

Definition at line 116 of file itkImageGaussianModelEstimator.h.

◆ TrainingImageConstPointer

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::TrainingImageConstPointer = typename TTrainingImage::ConstPointer

Definition at line 102 of file itkImageGaussianModelEstimator.h.

◆ TrainingImageIterator

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::TrainingImageIterator = ImageRegionIterator<TTrainingImage>

Definition at line 115 of file itkImageGaussianModelEstimator.h.

◆ TrainingImagePixelType

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::TrainingImagePixelType = typename TTrainingImage::PixelType

Type definitions for the vector holding training image pixel type.

Definition at line 110 of file itkImageGaussianModelEstimator.h.

◆ TrainingImagePointer

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::TrainingImagePointer = typename TTrainingImage::Pointer

Definition at line 101 of file itkImageGaussianModelEstimator.h.

◆ TrainingImageType

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
using itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::TrainingImageType = TTrainingImage

Type definitions for the training image.

Definition at line 100 of file itkImageGaussianModelEstimator.h.

Constructor & Destructor Documentation

◆ ImageGaussianModelEstimator()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::ImageGaussianModelEstimator ( )
protecteddefault

◆ ~ImageGaussianModelEstimator()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::~ImageGaussianModelEstimator ( )
overrideprotecteddefault

Member Function Documentation

◆ EstimateGaussianModelParameters()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
void itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::EstimateGaussianModelParameters ( )
private

◆ EstimateModels()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
void itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::EstimateModels ( )
overrideprivatevirtual

Generate the model based on the training input data. Achieves the goal of training the classifier. Takes the set of training images and internally computes the means and variance of the various classes defined in the training set.

Implements itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >.

◆ GenerateData()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
void itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::GenerateData ( )
overrideprotectedvirtual

Starts the image modeling process

Reimplemented from itk::LightProcessObject.

◆ GetModifiableTrainingImage()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
virtual TrainingImageType* itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::GetModifiableTrainingImage ( )
virtual

Get/Set the training image.

◆ itkOverrideGetNameOfClassMacro()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::itkOverrideGetNameOfClassMacro ( ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >  )

Run-time type information (and related methods).

◆ New()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
static Pointer itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::New ( )
static

Method for creation through the object factory.

◆ PrintSelf()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
void itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::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::LightProcessObject.

◆ SetTrainingImage()

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
virtual void itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::SetTrainingImage ( TrainingImageType _arg)
virtual

Get/Set the training image.

Member Data Documentation

◆ m_Covariance

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
std::unique_ptr<MatrixType[]> itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::m_Covariance { nullptr }
private

Definition at line 158 of file itkImageGaussianModelEstimator.h.

◆ m_Means

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
MatrixType itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::m_Means {}
private

Definition at line 157 of file itkImageGaussianModelEstimator.h.

◆ m_NumberOfSamples

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
MatrixType itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::m_NumberOfSamples {}
private

Definition at line 156 of file itkImageGaussianModelEstimator.h.

◆ m_TrainingImage

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
TrainingImagePointer itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::m_TrainingImage {}
private

Definition at line 160 of file itkImageGaussianModelEstimator.h.

◆ VectorDimension

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
constexpr unsigned int itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::VectorDimension = InputImagePixelType::Dimension
staticconstexprprivate

Dimension of each individual pixel vector.

Definition at line 143 of file itkImageGaussianModelEstimator.h.


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