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itk::SegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType, TOutputImage > Class Template Reference

A base class which defines the API for implementing a special class of image segmentation filters using level set methods. More...

#include <itkSegmentationLevelSetImageFilter.h>

Inheritance diagram for itk::SegmentationLevelSetImageFilter:

[legend]Collaboration diagram for itk::SegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType, TOutputImage >:

[legend]List of all members.

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void	SetMaximumPropagationTimeStep (double n)
double	GetMaximumPropagationTimeStep () const
virtual	~SegmentationLevelSetImageFilter ()
	SegmentationLevelSetImageFilter (const Self &)
	SegmentationLevelSetImageFilter ()
Public Types
typedef SegmentationLevelSetImageFilter	Self
typedef SparseFieldLevelSetImageFilter< TInputImage, TOutputImage >	Superclass
typedef SmartPointer< Self >	Pointer
typedef SmartPointer< const Self >	ConstPointer
typedef Superclass::ValueType	ValueType
typedef Superclass::IndexType	IndexType
typedef Superclass::TimeStepType	TimeStepType
typedef Superclass::InputImageType	InputImageType
typedef TOutputImage	OutputImageType
typedef TFeatureImage	FeatureImageType
typedef SegmentationLevelSetFunction< OutputImageType, FeatureImageType >	SegmentationFunctionType
typedef SegmentationFunctionType::VectorImageType	VectorImageType
Public Methods
virtual const char *	GetClassName () const
virtual void	SetInitialImage (InputImageType *f)
virtual const SegmentationFunctionType::ImageType *	GetSpeedImage () const
virtual const SegmentationFunctionType::VectorImageType *	GetAdvectionImage () const

virtual void	SetMaximumRMSError (ValueType _arg)
virtual ValueType	GetMaximumRMSError ()

virtual void	SetMaximumIterations (unsigned int _arg)
virtual unsigned int	GetMaximumIterations ()

virtual void	SetFeatureImage (const FeatureImageType *f)
virtual FeatureImageType *	GetFeatureImage ()

void	SetUseNegativeFeaturesOn ()
void	SetUseNegativeFeaturesOff ()

void	SetUseNegativeFeatures (bool u)
bool	GetUseNegativeFeatures () const

virtual void	SetReverseExpansionDirection (bool _arg)
virtual bool	GetReverseExpansionDirection ()
virtual void	ReverseExpansionDirectionOn ()
virtual void	ReverseExpansionDirectionOff ()

void	SetFeatureScaling (ValueType v)

void	SetPropagationScaling (ValueType v)
ValueType	GetPropagationScaling () const

void	SetAdvectionScaling (ValueType v)
ValueType	GetAdvectionScaling () const

void	SetCurvatureScaling (ValueType v)
ValueType	GetCurvatureScaling () const

void	SetUseMinimalCurvature (bool b)
bool	GetUseMinimalCurvature () const
void	UseMinimalCurvatureOn ()
void	UseMinimalCurvatureOff ()

virtual void	SetSegmentationFunction (SegmentationFunctionType *s)
virtual SegmentationFunctionType *	GetSegmentationFunction ()

void	SetMaximumCurvatureTimeStep (double n)
double	GetMaximumCurvatureTimeStep () const
Protected Methods
virtual void	PrintSelf (std::ostream &os, Indent indent) const
void	GenerateData ()
bool	Halt ()

virtual void	InitializeIteration ()
Protected Attributes
bool	m_ReverseExpansionDirection

Detailed Description

template<class TInputImage, class TFeatureImage, class TOutputPixelType = float, class TOutputImage = Image<TOutputPixelType, ::itk::GetImageDimension<TInputImage>::ImageDimension>>
class itk::SegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType, TOutputImage >

A base class which defines the API for implementing a special class of image segmentation filters using level set methods.

OVERVIEW: This object defines the framework for a class of segmentation filters which use level set methods. These filters work by constructing a ``feature image'' onto which the evolving level set locks as it moves. In the feature image, values that are close to zero are associated with object boundaries. An original (or preprocessed) image is given to the filter as the feature image and a seed for the level set is given as the input of the filter. The seed is converted into a level set embedding which propagates according to the features calculated from the original image.

TEMPLATE PARAMETERS: There are two required and two optional template parameter for these filters. Of the optional parameters, the last, TOutputImage, should not be changed from its default. It is only there to instantiate the parent class correctly.

TInputImage is the image type of the initial model you will input to the filter using SetInput() or SetInitialImage().

TFeatureImage is the image type of the image from which the filter will calculate the speed term for segmentation (see INPUTS).

TOutputPixelType is the data type used for the output image phi, the implicit level set image. This should really only ever be set as float (default) or double.

INPUTS: The input to any subclass of this filter is the seed image for the initial level set embedding. As with other subclasses of the SparseLevelSetImageFilter, the type of the input image is is not important. The (RequestedRegion) size of the seed image must, however, match the (RequestedRegion) size of the feature image.

You must identify the initial front (surface) in the input image. You do this by specifying its isovalue through the method SetIsoSurfaceValue(float f). The algorithm will then initialize its solution using the front represented by value f. Note that the front is always represented by isosurface zero in the output and not the isosurface you specified for the input. This is because, for simplicity, the filter will shift your input image so that the active front has zero values.

A NOTE ON DATA SPACING: Input data with anisotropic spacing should be resampled to isotropic voxels for use in this filter. Interpolation has not been built into the underlying p.d.e. solver.
Depending on the particular application and filter that you are using, the feature image should be preprocessed with some type of noise reduction filtering. The feature image input can be of any type, but it will be cast to floating point before calculations are done.

OUTPUTS: The output of any subclass of this filter is a level set embedding as described in SparseFieldLevelSetImageFilter. The zero crossings of the output image give the pixels closest to the level set boundary. By ITK convention, NEGATIVE values are pixels INSIDE the segmented region and POSITIVE values are pixels OUTSIDE the segmented region.

PARAMETERS

The MaximumRMSChange parameter is used to determine when the solution has converged. A lower value will result in a tighter-fitting solution, but will require more computations. Too low a value could put the solver into an infinite loop unless a reasonable MaximumIterations parameter is set. Values should always be greater than 0.0 and less than 1.0.

The MaximumIterations parameter can be used to halt the solution after a specified number of iterations, overriding the MaximumRMSChange halting criteria.

The standard convention for ITK level-set segmentation filters is that POSITIVE propagation (speed) and advection terms cause the surface to EXPAND while negative terms cause the surface to CONTRACT. When the ReverseExpansionDirection parameter is set to TRUE (on), it tells the function object to reverse the standard ITK convention so that NEGATIVE terms cause EXPANSION and positive terms cause CONTRACTION.

This parameter can be safely changed as appropriate for a particular application or data set to achieve the desired behavior.

The FeatureScaling parameter controls the magnitude of the features calculated for use in the level set propagation and advection speeds. This value simply sets both parameters to equal values at once. Some filters may only use on of these two terms and this method is a generic way to set either or both without having to know which is in use.

The CurvatureScaling parameter controls the magnitude of the curvature values which are calculated on the evolving isophote. This is important in controlling the relative effect of curvature in the calculation. Default value is 1.0. Higher values relative to the other level set equation terms (propagation and advection) will give a smoother result.

The PropagationScaling parameter controls the scaling of the scalar propagation (speed) term relative to other terms in the level set equation. Setting this value will override any value already set by FeatureScaling.

The AdvectionScaling parameter controls the scaling of the vector advection field term relative to other terms in the level set equation. Setting this value will override any value already set by FeatureScaling.

See LevelSetFunction for more information.

Definition at line 147 of file itkSegmentationLevelSetImageFilter.h.

Member Typedef Documentation

template<class TInputImage, class TFeatureImage, class TOutputPixelType = float, class TOutputImage = Image<TOutputPixelType, ::itk::GetImageDimension<TInputImage>::ImageDimension>>

typedef SegmentationLevelSetFunction<OutputImageType, FeatureImageType> itk::SegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType, TOutputImage >::SegmentationFunctionType

The generic level set function type
Definition at line 170 of file itkSegmentationLevelSetImageFilter.h.

template<class TInputImage, class TFeatureImage, class TOutputPixelType = float, class TOutputImage = Image<TOutputPixelType, ::itk::GetImageDimension<TInputImage>::ImageDimension>>

typedef SegmentationFunctionType::VectorImageType itk::SegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType, TOutputImage >::VectorImageType

The type used for the advection field
Reimplemented in itk::CannySegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType >.
Definition at line 173 of file itkSegmentationLevelSetImageFilter.h.

Constructor & Destructor Documentation

Member Function Documentation

template<class TInputImage, class TFeatureImage, class TOutputPixelType = float, class TOutputImage = Image<TOutputPixelType, ::itk::GetImageDimension<TInputImage>::ImageDimension>>

virtual const SegmentationFunctionType::VectorImageType* itk::SegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType, TOutputImage >::GetAdvectionImage ( ) const [inline, virtual]

Definition at line 211 of file itkSegmentationLevelSetImageFilter.h.

template<class TInputImage, class TFeatureImage, class TOutputPixelType = float, class TOutputImage = Image<TOutputPixelType, ::itk::GetImageDimension<TInputImage>::ImageDimension>>

virtual const SegmentationFunctionType::ImageType* itk::SegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType, TOutputImage >::GetSpeedImage ( ) const [inline, virtual]

Definition at line 208 of file itkSegmentationLevelSetImageFilter.h.

Member Data Documentation

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

itkSegmentationLevelSetImageFilter.h

Generated at Tue Sep 16 11:41:17 2003 for ITK by

itk::SegmentationLevelSetImageFilter< TInputImage, TFeatureImage, TOutputPixelType, TOutputImage > Class Template Reference

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Public Types

Public Methods

Protected Methods