/usr/include/ITK-4.9/itkGeodesicActiveContourLevelSetFunction.h is in libinsighttoolkit4-dev 4.9.0-4ubuntu1.
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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 itkGeodesicActiveContourLevelSetFunction_h
#define itkGeodesicActiveContourLevelSetFunction_h
#include "itkSegmentationLevelSetFunction.h"
namespace itk
{
/** \class GeodesicActiveContourLevelSetFunction
*
* \brief This function is used in GeodesicActiveContourLevelSetImageFilter to
* segment structures in an image based on a user supplied edge potential map.
*
* \par IMPORTANT
* The LevelSetFunction class contain additional information necessary
* to gain full understanding of how to use this function.
*
* GeodesicActiveContourLevelSetFunction is a subclass of the generic LevelSetFunction.
* It is used to segment structures in an image based on a user supplied
* edge potential map \f$ g(I) \f$, which
* has values close to zero in regions near edges (or high image gradient) and values
* close to one in regions with relatively constant intensity. Typically, the edge
* potential map is a function of the gradient, for example:
*
* \f[ g(I) = 1 / ( 1 + | (\nabla * G)(I)| ) \f]
* \f[ g(I) = \exp^{-|(\nabla * G)(I)|} \f]
*
* where \f$ I \f$ is image intensity and
* \f$ (\nabla * G) \f$ is the derivative of Gaussian operator.
*
* The edge potential image is set via the SetFeatureImage() method.
*
* 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 such that:
*
* \f[ P(\mathbf{x}) = g(\mathbf{x}) \f]
* \f[ Z(\mathbf{x}) = g(\mathbf{x}) \f]
*
* An advection term \f$ \mathbf{A}(\mathbf{x}) \f$ is constructed
* from the negative gradient of the edge potential image.
*
* \f[ \mathbf{A}(\mathbf{x}) = -\nabla g(\mathbf{x}) \f]
*
* This term behaves like a doublet attracting the contour to the edges.
*
* This implementation is based on:
* "Geodesic Active Contours",
* V. Caselles, R. Kimmel and G. Sapiro.
* International Journal on Computer Vision,
* Vol 22, No. 1, pp 61-97, 1997
*
* \sa LevelSetFunction
* \sa SegmentationLevelSetImageFunction
* \sa GeodesicActiveContourLevelSetImageFilter
*
* \ingroup FiniteDifferenceFunctions
* \ingroup ITKLevelSets
*/
template< typename TImageType, typename TFeatureImageType = TImageType >
class GeodesicActiveContourLevelSetFunction:
public SegmentationLevelSetFunction< TImageType, TFeatureImageType >
{
public:
/** Standard class typedefs. */
typedef GeodesicActiveContourLevelSetFunction 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(GeodesicActiveContourLevelSetFunction, SegmentationLevelSetFunction);
/** Extract some parameters from the superclass. */
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 Superclass::FloatOffsetType FloatOffsetType;
typedef typename Superclass::VectorImageType VectorImageType;
typedef typename Superclass::GlobalDataStruct GlobalDataStruct;
/** Extract some parameters from the superclass. */
itkStaticConstMacro(ImageDimension, unsigned int,
Superclass::ImageDimension);
/** Compute speed image from feature image. */
virtual void CalculateSpeedImage() ITK_OVERRIDE;
/** Compute the advection field from feature image. */
virtual void CalculateAdvectionImage() ITK_OVERRIDE;
/** The curvature speed is same as the propagation speed. */
virtual ScalarValueType CurvatureSpeed(const NeighborhoodType & neighborhood,
const FloatOffsetType & offset, GlobalDataStruct *gd) const ITK_OVERRIDE
{
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) ITK_OVERRIDE
{
Superclass::Initialize(r);
this->SetAdvectionWeight(NumericTraits< ScalarValueType >::OneValue());
this->SetPropagationWeight(NumericTraits< ScalarValueType >::OneValue());
this->SetCurvatureWeight(NumericTraits< ScalarValueType >::OneValue());
}
protected:
GeodesicActiveContourLevelSetFunction()
{
this->SetAdvectionWeight(NumericTraits< ScalarValueType >::OneValue());
this->SetPropagationWeight(NumericTraits< ScalarValueType >::OneValue());
this->SetCurvatureWeight(NumericTraits< ScalarValueType >::OneValue());
m_DerivativeSigma = 1.0;
}
virtual ~GeodesicActiveContourLevelSetFunction() {}
GeodesicActiveContourLevelSetFunction(const Self &) ITK_DELETE_FUNCTION;
void operator=(const Self &) ITK_DELETE_FUNCTION;
void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE
{
Superclass::PrintSelf(os, indent);
os << indent << "DerivativeSigma: " << m_DerivativeSigma << std::endl;
}
private:
double m_DerivativeSigma;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGeodesicActiveContourLevelSetFunction.hxx"
#endif
#endif
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