/usr/include/ITK-4.5/itkCurvesLevelSetFunction.h is in libinsighttoolkit4-dev 4.5.0-3.
This file is owned by root:root, with mode 0o644.
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*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#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
* \ingroup ITKLevelSets
*/
template< typename TImageType, typename TFeatureImageType = TImageType >
class CurvesLevelSetFunction:
public SegmentationLevelSetFunction< TImageType, TFeatureImageType >
{
public:
/** Standard class typedefs. */
typedef CurvesLevelSetFunction Self;
typedef SegmentationLevelSetFunction< TImageType, TFeatureImageType > 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 this->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. */
OffsetValueType m_Center;
/** Stride length along the y-dimension. */
OffsetValueType m_xStride[ImageDimension];
double m_DerivativeSigma;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkCurvesLevelSetFunction.hxx"
#endif
#endif
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