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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 itkCannySegmentationLevelSetFunction_hxx
#define itkCannySegmentationLevelSetFunction_hxx
#include "itkGradientImageFilter.h"
#include "itkMultiplyImageFilter.h"
#include "itkImageRegionIterator.h"
#include "itkImageAlgorithm.h"
namespace itk
{
template <typename TImageType, typename TFeatureImageType>
void
CannySegmentationLevelSetFunction<TImageType, TFeatureImageType>::CalculateSpeedImage()
{
// Create a distance transform to the canny edges
this->CalculateDistanceImage();
// Graft the distance transform into the Speed Image
this->GetSpeedImage()->Graft(m_Distance->GetOutput());
}
template <typename TImageType, typename TFeatureImageType>
void
CannySegmentationLevelSetFunction<TImageType, TFeatureImageType>::CalculateAdvectionImage()
{
typename GradientImageFilter<ImageType, ScalarValueType, ScalarValueType>::Pointer gradient =
GradientImageFilter<ImageType, ScalarValueType, ScalarValueType>::New();
using CovariantVectorImageType =
typename GradientImageFilter<ImageType, ScalarValueType, ScalarValueType>::OutputImageType;
typename MultiplyImageFilter<CovariantVectorImageType, ImageType, CovariantVectorImageType>::Pointer multiply =
MultiplyImageFilter<CovariantVectorImageType, ImageType, CovariantVectorImageType>::New();
// Create a distance transform to the canny edges
this->CalculateDistanceImage();
gradient->SetInput(m_Distance->GetOutput());
gradient->Update();
multiply->SetInput1(gradient->GetOutput());
multiply->SetInput2(m_Distance->GetOutput());
// multiply->GraftOutput(dynamic_cast<CovariantVectorImageType
// *>(this->GetAdvectionImage()));
multiply->Update();
// Copy output to Advection Image
ImageAlgorithm::Copy(multiply->GetOutput(),
this->GetAdvectionImage(),
this->GetAdvectionImage()->GetRequestedRegion(),
this->GetAdvectionImage()->GetRequestedRegion());
}
template <typename TImageType, typename TFeatureImageType>
void
CannySegmentationLevelSetFunction<TImageType, TFeatureImageType>::CalculateDistanceImage()
{
auto tempFeature = TFeatureImageType::New();
// The minipipeline might muck with its feature image requested
// region. The rest of the class relies on the feature image requested
// region as specified by the original level set
// filter. We make a temporary shallow copy of feature image to
// build the distance image.
tempFeature->Graft(this->GetFeatureImage());
// AssignCannyInput either sets up a pipeline through the
// CastImageFilter if TImageType != TFeatureImageType
// or bypasses the Cast operation if TImageType == TFeatureType
typename TImageType::Pointer junk;
this->AssignCannyInput(tempFeature, junk);
m_Canny->SetUpperThreshold(m_Threshold);
m_Canny->SetVariance(m_Variance);
m_Canny->SetMaximumError(0.01);
m_Distance->SetInput(m_Canny->GetOutput());
m_Distance->GetOutput()->SetRequestedRegion(this->GetSpeedImage()->GetRequestedRegion());
m_Distance->Update();
}
} // end namespace itk
#endif
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