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itkVectorThresholdSegmentationLevelSetFunction.h
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itkVectorThresholdSegmentationLevelSetFunction.h
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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkVectorThresholdSegmentationLevelSetFunction.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 __itkVectorThresholdSegmentationLevelSetFunction_h_
#define __itkVectorThresholdSegmentationLevelSetFunction_h_
#include "itkSegmentationLevelSetFunction.h"
#include "itkNumericTraits.h"
#include "itkMahalanobisDistanceMembershipFunction.h"
namespace itk {
/** \class VectorThresholdSegmentationLevelSetFunction
*
* \brief This function is used in VectorThresholdSegmentationLevelSetImageFilter to
* segment structures in images based on the Mahalanobis distance.
*
* \par CREDITS
* This class was contributed to ITK by Stefan Lindenau
* http://www.itk.org/pipermail/insight-users/2003-December/005969.html
*
* \par SegmentationLevelSetFunction is a subclass of the generic LevelSetFunction.
* It useful for segmentations based on intensity values in an image. It works
* by constructing a speed term (feature image) with positive values inside an
* intensity window (between a low and high threshold) and negative values
* outside that intensity window. The evolving level set front will lock onto
* regions that are at the edges of the intensity window.
*
*
* \par
* Image \f$ f(x) \f$ is thresholded pixel by pixel using threshold \f$T\f$
* according to the following formula.
*
* \par
* \f[
* f(x) = T - MahalanobisDistance(x)
* \f]
*
* \sa SegmentationLevelSetImageFunction
* \sa ThresholdSegmentationLevelSetImageFilter
* \sa MahalanobisDistanceMembershipFunction*/
template <class TImageType, class TFeatureImageType>
class ITK_EXPORT VectorThresholdSegmentationLevelSetFunction
: public SegmentationLevelSetFunction<TImageType, TFeatureImageType>
{
public:
/** Standard class typedefs. */
typedef VectorThresholdSegmentationLevelSetFunction Self;
typedef SegmentationLevelSetFunction<TImageType, TFeatureImageType> Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
typedef TFeatureImageType FeatureImageType;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods) */
itkTypeMacro( VectorThresholdSegmentationLevelSetFunction, SegmentationLevelSetFunction );
/** Extract some parameters from the superclass. */
typedef typename Superclass::ImageType ImageType;
typedef typename Superclass::ScalarValueType ScalarValueType;
typedef typename Superclass::FeatureScalarType FeatureScalarType;
typedef typename Superclass::RadiusType RadiusType;
/** Extract some parameters from the superclass. */
itkStaticConstMacro(ImageDimension, unsigned int,
Superclass::ImageDimension);
/** Extract the number of components in the vector pixel type . */
typedef typename FeatureImageType::PixelType FeatureImagePixelType;
itkStaticConstMacro(NumberOfComponents, unsigned int,
FeatureImagePixelType::Dimension);
typedef Statistics::MahalanobisDistanceMembershipFunction<FeatureScalarType> MahalanobisFunctionType;
typedef typename MahalanobisFunctionType::Pointer MahalanobisFunctionPointer;
typedef typename MahalanobisFunctionType::MeanVectorType MeanVectorType;
typedef typename MahalanobisFunctionType::CovarianceMatrixType CovarianceMatrixType;
/** Set/Get mean and covariance */
void SetMean(const MeanVectorType &mean)
{ m_Mahalanobis->SetMean(mean); }
const MeanVectorType & GetMean() const
{ return m_Mahalanobis->GetMean(); }
void SetCovariance(const CovarianceMatrixType &cov)
{ m_Mahalanobis->SetCovariance(cov); }
const CovarianceMatrixType & GetCovariance() const
{ return m_Mahalanobis->GetCovariance(); }
/** Set/Get the threshold value for the MahanalobisDistance */
void SetThreshold(ScalarValueType thr)
{
m_Threshold = thr;
}
ScalarValueType GetThreshold()
{
return m_Threshold;
}
virtual void CalculateSpeedImage();
virtual void Initialize(const RadiusType &r)
{
Superclass::Initialize(r);
this->SetAdvectionWeight( NumericTraits<ScalarValueType>::Zero);
this->SetPropagationWeight(-1.0 * NumericTraits<ScalarValueType>::One);
this->SetCurvatureWeight(NumericTraits<ScalarValueType>::One);
}
protected:
VectorThresholdSegmentationLevelSetFunction()
{
MeanVectorType mean( NumberOfComponents );
CovarianceMatrixType covariance( NumberOfComponents, NumberOfComponents );
mean.fill(NumericTraits<ITK_TYPENAME FeatureScalarType::ValueType>::Zero);
covariance.fill(NumericTraits<ITK_TYPENAME FeatureScalarType::ValueType>::Zero);
m_Mahalanobis = MahalanobisFunctionType::New();
m_Mahalanobis->SetMean(mean);
m_Mahalanobis->SetCovariance(covariance);
this->SetAdvectionWeight(0.0);
this->SetPropagationWeight(1.0);
this->SetThreshold(1.8);
}
virtual ~VectorThresholdSegmentationLevelSetFunction(){}
VectorThresholdSegmentationLevelSetFunction(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
void PrintSelf(std::ostream& os, Indent indent) const
{
Superclass::PrintSelf(os, indent );
os << indent << "MahalanobisFunction: " << m_Mahalanobis << std::endl;
os << indent << "ThresholdValue: " << m_Threshold << std::endl;
}
MahalanobisFunctionPointer m_Mahalanobis;
ScalarValueType m_Threshold;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkVectorThresholdSegmentationLevelSetFunction.txx"
#endif
#endif