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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 itkCurvesLevelSetFunction_hxx
#define itkCurvesLevelSetFunction_hxx
#include "itkMath.h"
#include "itkImageRegionIterator.h"
#include "itkGradientRecursiveGaussianImageFilter.h"
#include "itkGradientImageFilter.h"
#include "itkCastImageFilter.h"
#include "itkImageAlgorithm.h"
namespace itk
{
template <typename TImageType, typename TFeatureImageType>
void
CurvesLevelSetFunction<TImageType, TFeatureImageType>::Initialize(const RadiusType & r)
{
Superclass::Initialize(r);
this->SetAdvectionWeight(NumericTraits<ScalarValueType>::OneValue());
this->SetPropagationWeight(NumericTraits<ScalarValueType>::OneValue());
this->SetCurvatureWeight(NumericTraits<ScalarValueType>::OneValue());
}
template <typename TImageType, typename TFeatureImageType>
void
CurvesLevelSetFunction<TImageType, TFeatureImageType>::CalculateSpeedImage()
{
/* copy the feature image into the speed image */
ImageAlgorithm::Copy(this->GetFeatureImage(),
this->GetSpeedImage(),
this->GetFeatureImage()->GetRequestedRegion(),
this->GetFeatureImage()->GetRequestedRegion());
}
template <typename TImageType, typename TFeatureImageType>
void
CurvesLevelSetFunction<TImageType, TFeatureImageType>::CalculateAdvectionImage()
{
/* compute the gradient of the feature image. */
typename VectorImageType::Pointer gradientImage;
if (Math::NotAlmostEquals(m_DerivativeSigma, 0.0f))
{
using DerivativeFilterType = GradientRecursiveGaussianImageFilter<FeatureImageType, VectorImageType>;
auto derivative = DerivativeFilterType::New();
derivative->SetInput(this->GetFeatureImage());
derivative->SetSigma(m_DerivativeSigma);
derivative->Update();
gradientImage = derivative->GetOutput();
}
else
{
using DerivativeFilterType = GradientImageFilter<FeatureImageType>;
auto derivative = DerivativeFilterType::New();
derivative->SetInput(this->GetFeatureImage());
derivative->UseImageSpacingOn();
derivative->Update();
using DerivativeOutputImageType = typename DerivativeFilterType::OutputImageType;
using GradientCasterType = CastImageFilter<DerivativeOutputImageType, VectorImageType>;
auto caster = GradientCasterType::New();
caster->SetInput(derivative->GetOutput());
caster->Update();
gradientImage = caster->GetOutput();
}
/* copy negative gradient into the advection image. */
ImageRegionIterator<VectorImageType> dit(gradientImage, this->GetFeatureImage()->GetRequestedRegion());
ImageRegionIterator<VectorImageType> ait(this->GetAdvectionImage(), this->GetFeatureImage()->GetRequestedRegion());
for (dit.GoToBegin(), ait.GoToBegin(); !dit.IsAtEnd(); ++dit, ++ait)
{
typename VectorImageType::PixelType v = dit.Get();
for (unsigned int j = 0; j < ImageDimension; ++j)
{
v[j] *= -1.0L;
}
ait.Set(v);
}
}
} // end namespace itk
#endif
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