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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkGeodesicActiveContourShapePriorLevelSetImageFilter.h,v $
Language: C++
Date: $Date: 2003-09-10 14:28:31 $
Version: $Revision: 1.2 $
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 __itkGeodesicActiveContourShapePriorLevelSetImageFilter_h_
#define __itkGeodesicActiveContourShapePriorLevelSetImageFilter_h_
#include "itkShapePriorSegmentationLevelSetImageFilter.h"
#include "itkGeodesicActiveContourShapePriorLevelSetFunction.h"
#include "itkShapePriorMAPCostFunction.h"
namespace itk {
/** \class GeodesicActiveContourShapePriorLevelSetImageFilter
* \brief Segments structures in an image based on a user supplied edge potential map
* and user supplied shape model.
*
* \par IMPORTANT
* The SegmentationLevelSetImageFilter class, ShapePriorSegmentationLevelSetImageFilter
* class and the
* GeodesicActiveContourShapePrior0LevelSetFunction class contain additional
* information necessary to gain full understanding of how to use this filter.
*
* \par OVERVIEW
* This class is a level set method segmentation filter. An initial contour
* is propagated outwards (or inwards) until it ''sticks'' to the shape boundaries.
* This is done by using a level set speed function based on a user supplied
* edge potential map and a user supplied shape model.
*
* \par INPUTS
* This filter requires two inputs. The first input is a initial level set.
* The initial level set is a real image which contains the initial contour/surface
* as the zero level set. For example, a signed distance function from the initial
* contour/surface is typically used. Unlike the simpler ShapeDetectionLevelSetImageFilter
* the initial contour does not have to lie wholly within the shape to be segmented.
* The intiial contour is allow to overlap the shape boundary. The advection term
* in the update equation behaves like a doublet and attracts the contour to the boundary.
* The shape prior term adds robustness by incorporating aprior information about
* the shape to be segmented.
* This approach for segmentation follows that of Leventon et al (2000).
*
* \par
* The second input is the feature image. For this filter, this is the edge
* potential map. General characteristics of an edge potential map is that
* it has values close to zero in regions near the edges and values close
* to one inside the shape itself. Typically, the edge potential map is compute
* from the image gradient, for example:
*
* \f[ g(I) = 1 / ( 1 + | (\nabla * G)(I)| ) \f]
* \f[ g(I) = \exp^{-|(\nabla * G)(I)|} \f]
*
* where \f$ I \f$ is image intensity and
* \f$ (\nabla * G) \f$ is the derivative of Gaussian operator.
*
* \par
* See SegmentationLevelSetImageFilter and SparseFieldLevelSetImageFilter
* for more information on Inputs.
*
* \par PARAMETERS
* The PropagationScaling parameter can be used to switch from propagation outwards
* (POSITIVE scaling parameter) versus propagating inwards (NEGATIVE scaling
* parameter).
*
* This implementation allows the user to set the weights between the propagation, advection
* curvature and shape prior term using methods SetPropagationScaling(), SetAdvectionScaling(),
* SetCurvatureScaling() and SetShapePriorScaling. In general, the larger the CurvatureScaling,
* the smoother the
* resulting contour. To follow the implementation in Leventon et al paper,
* set the PropagationScaling to \f$ \lambda_1 \times c \f$,
* the AdvectionScaling and CurvatureScaling both to \f$ \lambda_1 \f$ and
* the ShapePriorScaling to \f$ \lambda_2 \f$.
*
* \par OUTPUTS
* The filter outputs a single, scalar, real-valued image.
* Negative values in the output image represent the inside of the segmented region
* and positive values in the image represent the outside of the segmented region. The
* zero crossings of the image correspond to the position of the propagating
* front.
*
* \par
* See SparseFieldLevelSetImageFilter and
* SegmentationLevelSetImageFilter for more information.
*
* \par REFERENCES
* \par
* Leventon, M.E. et al. "Statistical Shape Influence in Geodesic Active Contours", CVPR 2000.
*
* \sa SegmentationLevelSetImageFilter
* \sa ShapePriorSegmentationLevelSetImageFilter
* \sa GeodesicActiveContourShapePriorLevelSetFunction
* \sa SparseFieldLevelSetImageFilter
* \sa ShapeSignedDistanceFunction
*
* \ingroup LevelSetSegmentation
*/
template <class TInputImage,
class TFeatureImage,
class TOutputPixelType = float >
class ITK_EXPORT GeodesicActiveContourShapePriorLevelSetImageFilter
: public ShapePriorSegmentationLevelSetImageFilter< TInputImage, TFeatureImage,
TOutputPixelType >
{
public:
/** Standard class typedefs */
typedef GeodesicActiveContourShapePriorLevelSetImageFilter Self;
typedef ShapePriorSegmentationLevelSetImageFilter< TInputImage, TFeatureImage,
TOutputPixelType > Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Inherited typedef from the superclass. */
typedef typename Superclass::ValueType ValueType;
typedef typename Superclass::OutputImageType OutputImageType;
typedef typename Superclass::FeatureImageType FeatureImageType;
typedef typename Superclass::OutputPixelType OutputPixelType;
/** Type of the segmentation function */
typedef GeodesicActiveContourShapePriorLevelSetFunction< OutputImageType,
FeatureImageType >
GeodesicActiveContourFunctionType;
typedef typename GeodesicActiveContourFunctionType::Pointer
GeodesicActiveContourFunctionPointer;
/** Run-time type information (and related methods). */
itkTypeMacro(GeodesicActiveContourShapePriorLevelSetImageFilter,
ShapePriorSegmentationLevelSetImageFilter);
/** Method for creation through the object factory */
itkNewMacro(Self);
/** Set the value of sigma used to compute the edge potential map derivatives */
void SetDerivativeSigma( float value )
{
if ( value != m_GeodesicActiveContourFunction->GetDerivativeSigma() )
{
m_GeodesicActiveContourFunction->SetDerivativeSigma( value );
this->Modified();
}
}
/** Get the value of sigma used to compute the edge potential map derivatives. */
float GetDerivativeSigma() const
{ return m_GeodesicActiveContourFunction->GetDerivativeSigma(); }
protected:
~GeodesicActiveContourShapePriorLevelSetImageFilter() {}
GeodesicActiveContourShapePriorLevelSetImageFilter();
virtual void PrintSelf(std::ostream &os, Indent indent) const;
GeodesicActiveContourShapePriorLevelSetImageFilter(const Self &); // purposely not implemented
void operator=(const Self&); //purposely not implemented
/** Overridden from Superclass to handle the case when PropagationScaling is zero
* and CurvatureScaling is non-zero.*/
void GenerateData();
private:
GeodesicActiveContourFunctionPointer m_GeodesicActiveContourFunction;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGeodesicActiveContourShapePriorLevelSetImageFilter.txx"
#endif
#endif
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