/usr/include/InsightToolkit/Algorithms/itkCurvesLevelSetFunction.h is in libinsighttoolkit3-dev 3.20.1-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 | /*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkCurvesLevelSetFunction.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 __itkCurvesLevelSetFunction_h
#define __itkCurvesLevelSetFunction_h
#include "itkSegmentationLevelSetFunction.h"
namespace itk {
/** \class CurvesLevelSetFunction
*
* \brief This function is used in CurvesLevelSetImageFilter to
* segment structures in images based on user supplied edge potential map.
*
* \par CurvesLevelSetFunction is a subclass of the generic LevelSetFunction.
* It is useful for segmentations based on a user supplied edge potential map which
* has values close to zero in regions near edges (or high image gradient) and values
* close to one in regions with relatively constant intensity. Typically, the edge
* potential map is a function of the 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 In this function both the propagation term \f$ P(\mathbf{x}) \f$
* and the curvature spatial modifier term $\f$ Z(\mathbf{x}) \f$ are taken directly
* from the edge potential image. The edge potential image is set via the
* SetFeatureImage() method. An advection term \f$ A(\mathbf{x}) \f$ is constructed
* from the negative gradient of the edge potential image. This term behaves like
* a doublet attracting the contour to the edges.
*
* \par This implementation is based on:
* L. Lorigo, O. Faugeras, W.E.L. Grimson, R. Keriven, R. Kikinis, A. Nabavi,
* and C.-F. Westin, Curves: Curve evolution for vessel segmentation.
* Medical Image Analysis, 5:195-206, 2001.
*
* \sa LevelSetFunction
* \sa SegmentationLevelSetImageFunction
* \sa GeodesicActiveContourLevelSetImageFilter
*
* \ingroup FiniteDifferenceFunctions
*/
template <class TImageType, class TFeatureImageType = TImageType>
class ITK_EXPORT CurvesLevelSetFunction
: public SegmentationLevelSetFunction<TImageType, TFeatureImageType>
{
public:
/** Standard class typedefs. */
typedef CurvesLevelSetFunction Self;
typedef SegmentationLevelSetFunction<TImageType> Superclass;
typedef LevelSetFunction<TImageType> SuperSuperclass;
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( CurvesLevelSetFunction, SegmentationLevelSetFunction );
/** Extract some parameters from the superclass. */
typedef typename SuperSuperclass::PixelType PixelType;
typedef typename Superclass::ImageType ImageType;
typedef typename Superclass::NeighborhoodType NeighborhoodType;
typedef typename Superclass::ScalarValueType ScalarValueType;
typedef typename Superclass::FeatureScalarType FeatureScalarType;
typedef typename Superclass::RadiusType RadiusType;
typedef typename SuperSuperclass::FloatOffsetType FloatOffsetType;
typedef typename SuperSuperclass::GlobalDataStruct GlobalDataStruct;
typedef typename Superclass::VectorImageType VectorImageType;
/** Extract some parameters from the superclass. */
itkStaticConstMacro(ImageDimension, unsigned int,
Superclass::ImageDimension);
/** Compute speed image from feature image. */
virtual void CalculateSpeedImage();
/** Compute the advection field from feature image. */
virtual void CalculateAdvectionImage();
/** The curvature speed is same as the propagation speed. */
virtual ScalarValueType CurvatureSpeed(const NeighborhoodType & neighborhood,
const FloatOffsetType & offset, GlobalDataStruct *gd ) const
{ return PropagationSpeed( neighborhood, offset, gd ); }
/** Set/Get the sigma for the Gaussian kernel used to compute the gradient
* of the feature image needed for the advection term of the equation. */
void SetDerivativeSigma( const double v )
{ m_DerivativeSigma = v; }
double GetDerivativeSigma()
{ return m_DerivativeSigma; }
virtual void Initialize(const RadiusType &r);
protected:
CurvesLevelSetFunction()
{
//Curvature term is the minimal curvature.
this->UseMinimalCurvatureOn();
this->SetAdvectionWeight( NumericTraits<ScalarValueType>::One );
this->SetPropagationWeight( NumericTraits<ScalarValueType>::One );
this->SetCurvatureWeight( NumericTraits<ScalarValueType>::One );
m_DerivativeSigma = 1.0;
}
virtual ~CurvesLevelSetFunction() {}
CurvesLevelSetFunction(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 << "DerivativeSigma: " << m_DerivativeSigma << std::endl;
}
private:
/** Slices for the ND neighborhood. */
std::slice x_slice[ImageDimension];
/** The offset of the center pixel in the neighborhood. */
::size_t m_Center;
/** Stride length along the y-dimension. */
::size_t m_xStride[ImageDimension];
double m_DerivativeSigma;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkCurvesLevelSetFunction.txx"
#endif
#endif
|