ITK  4.6.0
Insight Segmentation and Registration 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>

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

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 calcualted 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:
Segmentation/GibbsPriorImageFilter1.cxx.

Definition at line 77 of file itkImageGaussianModelEstimator.h.

Public Types

typedef SmartPointer< const SelfConstPointer
 
typedef
ImageRegionConstIterator
< TInputImage > 
InputImageConstIterator
 
typedef TInputImage::ConstPointer InputImageConstPointer
 
typedef ImageRegionIterator
< TInputImage > 
InputImageIterator
 
typedef TInputImage::PixelType InputImagePixelType
 
typedef TInputImage::Pointer InputImagePointer
 
typedef TInputImage InputImageType
 
typedef
TMembershipFunction::Pointer 
MembershipFunctionPointer
 
typedef TMembershipFunction MembershipFunctionType
 
typedef SmartPointer< SelfPointer
 
typedef ImageGaussianModelEstimator Self
 
typedef
ImageModelEstimatorBase
< TInputImage,
TMembershipFunction > 
Superclass
 
typedef
ImageRegionConstIterator
< TTrainingImage > 
TrainingImageConstIterator
 
typedef
TTrainingImage::ConstPointer 
TrainingImageConstPointer
 
typedef ImageRegionIterator
< TTrainingImage > 
TrainingImageIterator
 
typedef TTrainingImage::PixelType TrainingImagePixelType
 
typedef TTrainingImage::Pointer TrainingImagePointer
 
typedef TTrainingImage TrainingImageType
 
- Public Types inherited from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >
typedef SmartPointer< const SelfConstPointer
 
typedef TInputImage::Pointer InputImagePointer
 
typedef TInputImage InputImageType
 
typedef
TMembershipFunction::Pointer 
MembershipFunctionPointer
 
typedef std::vector
< MembershipFunctionPointer
MembershipFunctionPointerVector
 
typedef SmartPointer< SelfPointer
 
typedef ImageModelEstimatorBase Self
 
typedef LightProcessObject Superclass
 
- Public Types inherited from itk::LightProcessObject
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef LightProcessObject 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 void SetTrainingImage (TrainingImageType *_arg)
 
virtual TrainingImageTypeGetModifiableTrainingImage ()
 
virtual const TrainingImageTypeGetTrainingImage () const
 
- 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
 
void SetMembershipFunctions (MembershipFunctionPointerVector membershipFunctions)
 
virtual void SetNumberOfModels (unsigned int _arg)
 
void Update ()
 
virtual void SetInputImage (InputImageType *_arg)
 
virtual InputImageTypeGetModifiableInputImage ()
 
virtual const InputImageTypeGetInputImage () const
 
- Public Member Functions inherited from itk::LightProcessObject
virtual void AbortGenerateDataOff ()
 
virtual void AbortGenerateDataOn ()
 
virtual const bool & GetAbortGenerateData () const
 
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
 
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::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 flag)
 
- Static Public Member Functions inherited from itk::LightObject
static void BreakOnError ()
 
static Pointer New ()
 

Protected Member Functions

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

typedef TInputImage::SizeType InputImageSizeType
 
typedef vnl_matrix< double > MatrixType
 

Private Member Functions

void EstimateGaussianModelParameters ()
 
virtual void EstimateModels ()
 
 ImageGaussianModelEstimator (const Self &)
 
void operator= (const Self &)
 

Private Attributes

MatrixTypem_Covariance
 
MatrixType m_Means
 
MatrixType m_NumberOfSamples
 
TrainingImagePointer m_TrainingImage
 

Static Private Attributes

static const unsigned int VectorDimension = InputImagePixelType::Dimension
 

Additional Inherited Members

- Protected Types inherited from itk::LightObject
typedef int InternalReferenceCountType
 
- Protected Attributes inherited from itk::LightObject
InternalReferenceCountType m_ReferenceCount
 
SimpleFastMutexLock m_ReferenceCountLock
 

Member Typedef Documentation

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

Definition at line 85 of file itkImageGaussianModelEstimator.h.

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

Definition at line 113 of file itkImageGaussianModelEstimator.h.

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

Definition at line 96 of file itkImageGaussianModelEstimator.h.

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

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

Definition at line 112 of file itkImageGaussianModelEstimator.h.

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

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

Definition at line 105 of file itkImageGaussianModelEstimator.h.

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

Definition at line 95 of file itkImageGaussianModelEstimator.h.

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

Definition at line 140 of file itkImageGaussianModelEstimator.h.

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

Type definition for the input image.

Definition at line 91 of file itkImageGaussianModelEstimator.h.

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

Definition at line 138 of file itkImageGaussianModelEstimator.h.

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

Definition at line 119 of file itkImageGaussianModelEstimator.h.

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

Type definitions for the membership function .

Definition at line 118 of file itkImageGaussianModelEstimator.h.

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

Definition at line 84 of file itkImageGaussianModelEstimator.h.

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

Standard class typedefs.

Definition at line 82 of file itkImageGaussianModelEstimator.h.

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

Definition at line 83 of file itkImageGaussianModelEstimator.h.

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

Definition at line 115 of file itkImageGaussianModelEstimator.h.

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

Definition at line 101 of file itkImageGaussianModelEstimator.h.

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

Definition at line 114 of file itkImageGaussianModelEstimator.h.

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

Type definitions for the vector holding training image pixel type.

Definition at line 109 of file itkImageGaussianModelEstimator.h.

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

Definition at line 100 of file itkImageGaussianModelEstimator.h.

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

Type definitions for the training image.

Definition at line 99 of file itkImageGaussianModelEstimator.h.

Constructor & Destructor Documentation

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::ImageGaussianModelEstimator ( )
protected
template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::~ImageGaussianModelEstimator ( )
protected
template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::ImageGaussianModelEstimator ( const Self )
private

Member Function Documentation

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
virtual::itk::LightObject::Pointer itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::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::LightProcessObject.

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

A function that generates the model based on the training input data. Achieves the goal of training the classifier.

Implements itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >.

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

Starts the image modelling process

Reimplemented from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >.

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

Get/Set the training image.

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
virtual const char* itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::GetNameOfClass ( ) const
virtual

Run-time type information (and related methods).

Reimplemented from itk::ImageModelEstimatorBase< TInputImage, TMembershipFunction >.

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

Get/Set the training image.

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

Method for creation through the object factory.

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
void itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::operator= ( const Self )
private
template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
virtual void itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::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::ImageModelEstimatorBase< TInputImage, TMembershipFunction >.

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

template<typename TInputImage , typename TMembershipFunction , typename TTrainingImage >
MatrixType* itk::ImageGaussianModelEstimator< TInputImage, TMembershipFunction, TTrainingImage >::m_Covariance
private

Definition at line 148 of file itkImageGaussianModelEstimator.h.

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

Definition at line 147 of file itkImageGaussianModelEstimator.h.

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

Definition at line 146 of file itkImageGaussianModelEstimator.h.

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

Definition at line 150 of file itkImageGaussianModelEstimator.h.

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

Dimension of each individual pixel vector.

Definition at line 144 of file itkImageGaussianModelEstimator.h.


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