/usr/include/InsightToolkit/Algorithms/itkThresholdSegmentationLevelSetFunction.txx is in libinsighttoolkit3-dev 3.20.1-1.
This file is owned by root:root, with mode 0o644.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | /*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkThresholdSegmentationLevelSetFunction.txx
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkThresholdSegmentationLevelSetFunction_txx
#define __itkThresholdSegmentationLevelSetFunction_txx
#include "itkThresholdSegmentationLevelSetFunction.h"
#include "itkImageRegionIterator.h"
#include "itkGradientAnisotropicDiffusionImageFilter.h"
#include "itkLaplacianImageFilter.h"
#include "itkImageFileWriter.h"
namespace itk {
template <class TImageType, class TFeatureImageType>
void ThresholdSegmentationLevelSetFunction<TImageType, TFeatureImageType>
::CalculateSpeedImage()
{
typename GradientAnisotropicDiffusionImageFilter<TFeatureImageType, TFeatureImageType>::Pointer
diffusion = GradientAnisotropicDiffusionImageFilter<TFeatureImageType, TFeatureImageType>::New();
typename LaplacianImageFilter<TFeatureImageType, TFeatureImageType>::Pointer
laplacian = LaplacianImageFilter<TFeatureImageType, TFeatureImageType>::New();
ImageRegionIterator<FeatureImageType> lit;
ImageRegionConstIterator<FeatureImageType>
fit(this->GetFeatureImage(), this->GetFeatureImage()->GetRequestedRegion());
ImageRegionIterator<ImageType>
sit(this->GetSpeedImage(), this->GetFeatureImage()->GetRequestedRegion());
if (m_EdgeWeight != 0.0)
{
diffusion->SetInput(this->GetFeatureImage());
diffusion->SetConductanceParameter(m_SmoothingConductance);
diffusion->SetTimeStep(m_SmoothingTimeStep);
diffusion->SetNumberOfIterations(m_SmoothingIterations);
laplacian->SetInput(diffusion->GetOutput());
laplacian->Update();
lit = ImageRegionIterator<FeatureImageType>(laplacian->GetOutput(),
this->GetFeatureImage()->GetRequestedRegion());
lit.GoToBegin();
}
// Copy the meta information (spacing and origin) from the feature image
this->GetSpeedImage()->CopyInformation(this->GetFeatureImage());
// Calculate the speed image
ScalarValueType upper_threshold = static_cast<ScalarValueType>(m_UpperThreshold);
ScalarValueType lower_threshold = static_cast<ScalarValueType>(m_LowerThreshold);
ScalarValueType mid = ( (upper_threshold - lower_threshold) / 2.0 ) + lower_threshold;
ScalarValueType threshold;
for ( fit.GoToBegin(), sit.GoToBegin(); ! fit.IsAtEnd(); ++sit, ++fit)
{
if (static_cast<ScalarValueType>(fit.Get()) < mid)
{
threshold = fit.Get() - lower_threshold;
}
else
{
threshold = upper_threshold - fit.Get();
}
if ( m_EdgeWeight != 0.0)
{
sit.Set( static_cast<ScalarValueType>(threshold + m_EdgeWeight * lit.Get()) );
++lit;
}
else
{
sit.Set( static_cast<ScalarValueType>(threshold) );
}
}
}
} // end namespace itk
#endif
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