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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 itkAnisotropicDiffusionImageFilter_hxx
#define itkAnisotropicDiffusionImageFilter_hxx
namespace itk
{
template <typename TInputImage, typename TOutputImage>
AnisotropicDiffusionImageFilter<TInputImage, TOutputImage>::AnisotropicDiffusionImageFilter()
{
this->SetNumberOfIterations(1);
m_ConductanceParameter = 1.0;
m_ConductanceScalingParameter = 1.0;
m_ConductanceScalingUpdateInterval = 1;
m_TimeStep = 0.5 / std::pow(2.0, static_cast<double>(ImageDimension));
m_FixedAverageGradientMagnitude = 1.0;
m_GradientMagnitudeIsFixed = false;
}
template <typename TInputImage, typename TOutputImage>
void
AnisotropicDiffusionImageFilter<TInputImage, TOutputImage>::InitializeIteration()
{
auto * f = dynamic_cast<AnisotropicDiffusionFunction<UpdateBufferType> *>(this->GetDifferenceFunction().GetPointer());
if (!f)
{
throw ExceptionObject(__FILE__, __LINE__, "Anisotropic diffusion function is not set.", ITK_LOCATION);
}
f->SetConductanceParameter(m_ConductanceParameter);
f->SetTimeStep(m_TimeStep);
// Check the timestep for stability
double minSpacing;
if (this->GetUseImageSpacing())
{
const auto & spacing = this->GetInput()->GetSpacing();
minSpacing = spacing[0];
for (unsigned int i = 1; i < ImageDimension; ++i)
{
if (spacing[i] < minSpacing)
{
minSpacing = spacing[i];
}
}
}
else
{
minSpacing = 1.0;
}
if (m_TimeStep > (minSpacing / std::pow(2.0, static_cast<double>(ImageDimension) + 1)))
{
// f->SetTimeStep(1.0 / std::pow(2.0,
// static_cast<double>(ImageDimension)));
itkWarningMacro("Anisotropic diffusion unstable time step: "
<< m_TimeStep << std::endl
<< "Stable time step for this image must be smaller than "
<< minSpacing / std::pow(2.0, static_cast<double>(ImageDimension + 1)));
}
if (m_GradientMagnitudeIsFixed == false)
{
if ((this->GetElapsedIterations() % m_ConductanceScalingUpdateInterval) == 0)
{
f->CalculateAverageGradientMagnitudeSquared(this->GetOutput());
}
}
else
{
f->SetAverageGradientMagnitudeSquared(m_FixedAverageGradientMagnitude * m_FixedAverageGradientMagnitude);
}
f->InitializeIteration();
if (this->GetNumberOfIterations() != 0)
{
this->UpdateProgress((static_cast<float>(this->GetElapsedIterations())) /
(static_cast<float>(this->GetNumberOfIterations())));
}
else
{
this->UpdateProgress(0);
}
}
template <typename TInputImage, typename TOutputImage>
void
AnisotropicDiffusionImageFilter<TInputImage, TOutputImage>::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "TimeStep: " << m_TimeStep << std::endl;
os << indent << "ConductanceParameter: " << m_ConductanceParameter << std::endl;
os << indent << "ConductanceScalingParameter: " << m_ConductanceScalingParameter << std::endl;
os << indent << "ConductanceScalingUpdateInterval: " << m_ConductanceScalingUpdateInterval << std::endl;
os << indent << "FixedAverageGradientMagnitude: " << m_FixedAverageGradientMagnitude << std::endl;
}
} // end namespace itk
#endif
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