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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 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
* https://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
* \ingroup ITKLevelSets
*/
template <typename TImageType, typename TFeatureImageType>
class ITK_TEMPLATE_EXPORT VectorThresholdSegmentationLevelSetFunction
: public SegmentationLevelSetFunction<TImageType, TFeatureImageType>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(VectorThresholdSegmentationLevelSetFunction);
/** Standard class type aliases. */
using Self = VectorThresholdSegmentationLevelSetFunction;
using Superclass = SegmentationLevelSetFunction<TImageType, TFeatureImageType>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
using FeatureImageType = TFeatureImageType;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(VectorThresholdSegmentationLevelSetFunction);
/** Extract some parameters from the superclass. */
using typename Superclass::ImageType;
using typename Superclass::ScalarValueType;
using typename Superclass::FeatureScalarType;
using typename Superclass::RadiusType;
/** Extract some parameters from the superclass. */
static constexpr unsigned int ImageDimension = Superclass::ImageDimension;
/** Extract the number of components in the vector pixel type . */
using FeatureImagePixelType = typename FeatureImageType::PixelType;
static constexpr unsigned int NumberOfComponents = FeatureImagePixelType::Dimension;
using MahalanobisFunctionType = Statistics::MahalanobisDistanceMembershipFunction<FeatureScalarType>;
using MahalanobisFunctionPointer = typename MahalanobisFunctionType::Pointer;
using MeanVectorType = typename MahalanobisFunctionType::MeanVectorType;
using CovarianceMatrixType = typename MahalanobisFunctionType::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 MahalanobisDistance */
void
SetThreshold(ScalarValueType thr)
{
m_Threshold = thr;
}
ScalarValueType
GetThreshold()
{
return m_Threshold;
}
void
CalculateSpeedImage() override;
void
Initialize(const RadiusType & r) override
{
Superclass::Initialize(r);
this->SetAdvectionWeight(ScalarValueType{});
this->SetPropagationWeight(-1.0 * NumericTraits<ScalarValueType>::OneValue());
this->SetCurvatureWeight(NumericTraits<ScalarValueType>::OneValue());
}
protected:
VectorThresholdSegmentationLevelSetFunction()
{
MeanVectorType mean(NumberOfComponents);
CovarianceMatrixType covariance(NumberOfComponents, NumberOfComponents);
mean.Fill(typename FeatureScalarType::ValueType{});
covariance.Fill(typename FeatureScalarType::ValueType{});
m_Mahalanobis = MahalanobisFunctionType::New();
m_Mahalanobis->SetMean(mean);
m_Mahalanobis->SetCovariance(covariance);
this->SetAdvectionWeight(0.0);
this->SetPropagationWeight(1.0);
this->SetThreshold(1.8);
}
~VectorThresholdSegmentationLevelSetFunction() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override
{
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.hxx"
#endif
#endif
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