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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkShapePriorSegmentationLevelSetImageFilter.h
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkShapePriorSegmentationLevelSetImageFilter_h
#define __itkShapePriorSegmentationLevelSetImageFilter_h
#include "itkSegmentationLevelSetImageFilter.h"
#include "itkShapePriorSegmentationLevelSetFunction.h"
#include "itkSingleValuedNonLinearOptimizer.h"
#include "itkShapePriorMAPCostFunctionBase.h"
namespace itk {
/**
*
* \class ShapePriorSegmentationLevelSetImageFilter
*
* \brief A base class which defines the API for implementing a level set
* segmentation filter with statistical shape influence.
*
* \par OVERVIEW
* This class extends the functionality of SegmentationLevelSetImageFilter
* with an additional statistical shape influence term in the level set evolution as
* developed in [1].
*
* \par TEMPLATE PARAMETERS
* There are two required and one optional template parameter for these
* filters.
*
* 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.
*
*
* \par PARAMETERS
*
* \par
* From a level set evolution point of view, the shape is represented by a
* signed distance function from the shape encapsulated in a ShapeSignedDistanceFunction
* object.
*
* \sa ShapeSignedDistanceFunction
* \sa ShapePriorSegmentationLevelSetFunction
*
* \par REFERENCES
* \par
* [1] Leventon, M.E. et al. "Statistical Shape Influence in Geodesic Active Contours", CVPR 2000.
*
*/
template <class TInputImage,
class TFeatureImage,
class TOutputPixelType = float >
class ITK_EXPORT ShapePriorSegmentationLevelSetImageFilter
: public SegmentationLevelSetImageFilter< TInputImage, TFeatureImage,
TOutputPixelType>
{
public:
/** Dimension of the input/level set image. */
itkStaticConstMacro(ImageDimension, unsigned int,
TInputImage::ImageDimension);
/** Standard class typedefs */
typedef ShapePriorSegmentationLevelSetImageFilter Self;
typedef SegmentationLevelSetImageFilter<TInputImage, TFeatureImage, TOutputPixelType>
Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Run-time type information (and related methods). */
itkTypeMacro(ShapePriorSegmentationLevelSetImageFilter, SegmentationLevelSetImageFilter);
/** Inherited typedef from the superclass. */
typedef typename Superclass::ValueType ValueType;
typedef typename Superclass::OutputImageType OutputImageType;
typedef typename Superclass::FeatureImageType FeatureImageType;
/** Type of the output pixel. */
typedef TOutputPixelType OutputPixelType;
/** The level set function with shape prior type */
typedef ShapePriorSegmentationLevelSetFunction<OutputImageType, FeatureImageType>
ShapePriorSegmentationFunctionType;
/** The shape signed distance function type. */
typedef typename ShapePriorSegmentationFunctionType::ShapeFunctionType
ShapeFunctionType;
typedef typename ShapeFunctionType::Pointer ShapeFunctionPointer;
/** The type of the MAP estimate cost function. */
typedef ShapePriorMAPCostFunctionBase<TFeatureImage,TOutputPixelType> CostFunctionType;
typedef typename CostFunctionType::Pointer CostFunctionPointer;
typedef typename CostFunctionType::ParametersType ParametersType;
/** Type of node used to represent the active region around the zero set. */
typedef typename CostFunctionType::NodeType NodeType;
typedef typename CostFunctionType::NodeContainerType NodeContainerType;
typedef typename NodeContainerType::Pointer NodeContainerPointer;
/** The type of optimizer used to compute the MAP estimate of the shape and pose parameters. */
typedef SingleValuedNonLinearOptimizer OptimizerType;
typedef typename OptimizerType::Pointer OptimizerPointer;
/** Set/Get the shape signed distance function. */
virtual void SetShapeFunction(ShapeFunctionType *s);
itkGetObjectMacro( ShapeFunction, ShapeFunctionType );
/** Set/Get the shape prior MAP cost function. */
itkSetObjectMacro( CostFunction, CostFunctionType );
itkGetObjectMacro( CostFunction, CostFunctionType );
/** Set/Get the optimizer. */
itkSetObjectMacro( Optimizer, OptimizerType );
itkGetObjectMacro( Optimizer, OptimizerType );
/** Set/Get the initial parameters. These are the initial parameters applied
* to the ShapeFunction. The user should refer to the documentation of
* the particular type of ShapeSignedDistanceFunction used to determine
* the meaning of the parameters. */
itkSetMacro( InitialParameters, ParametersType );
itkGetConstMacro( InitialParameters, ParametersType );
/** Set/Get the scaling of the shape prior term. */
void SetShapePriorScaling( ValueType v )
{
if ( v != m_ShapePriorSegmentationFunction->GetShapePriorWeight() )
{
m_ShapePriorSegmentationFunction->SetShapePriorWeight( v );
this->Modified();
}
}
ValueType GetShapePriorScaling() const
{
return m_ShapePriorSegmentationFunction->GetShapePriorWeight();
}
/** Set the shape prior segmentation function. In general, this should only be called
* by a subclass of this object. It is made public to allow itk::Command objects access. */
virtual void SetShapePriorSegmentationFunction( ShapePriorSegmentationFunctionType * s );
virtual ShapePriorSegmentationFunctionType * GetShapePriorSegmentationFunction()
{ return m_ShapePriorSegmentationFunction; }
/** Get the current parameters. */
itkGetConstReferenceMacro( CurrentParameters, ParametersType );
protected:
virtual ~ShapePriorSegmentationLevelSetImageFilter() {}
ShapePriorSegmentationLevelSetImageFilter();
virtual void PrintSelf(std::ostream& os, Indent indent) const;
/** Overrides parent implementation. MAP estimates of the shape and pose parameters
is computed in this method. */
virtual void InitializeIteration();
/** Overridden from ProcessObject to set certain values before starting the
* finite difference solver and then create an appropriate output */
void GenerateData();
/** Extract node of active region into a NodeContainer */
void ExtractActiveRegion( NodeContainerType * ptr );
private:
ShapePriorSegmentationLevelSetImageFilter(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
ShapeFunctionPointer m_ShapeFunction;
CostFunctionPointer m_CostFunction;
OptimizerPointer m_Optimizer;
ParametersType m_InitialParameters;
ParametersType m_CurrentParameters;
ShapePriorSegmentationFunctionType * m_ShapePriorSegmentationFunction;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkShapePriorSegmentationLevelSetImageFilter.txx"
#endif
#endif
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