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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 itkShapePriorSegmentationLevelSetFunction_hxx
#define itkShapePriorSegmentationLevelSetFunction_hxx
#include "itkMath.h"
namespace itk
{
template <typename TImageType, typename TFeatureImageType>
ShapePriorSegmentationLevelSetFunction<TImageType, TFeatureImageType>::ShapePriorSegmentationLevelSetFunction()
{
m_ShapeFunction = nullptr;
m_ShapePriorWeight = ScalarValueType{};
}
template <typename TImageType, typename TFeatureImageType>
void
ShapePriorSegmentationLevelSetFunction<TImageType, TFeatureImageType>::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
itkPrintSelfObjectMacro(ShapeFunction);
os << indent
<< "ShapePriorWeight: " << static_cast<typename NumericTraits<ScalarValueType>::PrintType>(m_ShapePriorWeight)
<< std::endl;
}
template <typename TImageType, typename TFeatureImageType>
auto
ShapePriorSegmentationLevelSetFunction<TImageType, TFeatureImageType>::ComputeUpdate(
const NeighborhoodType & neighborhood,
void * gd,
const FloatOffsetType & offset) -> PixelType
{
// Compute the generic level set update using superclass
PixelType value = this->Superclass::ComputeUpdate(neighborhood, gd, offset);
// Add the shape prior term
if (m_ShapeFunction && Math::NotExactlyEquals(m_ShapePriorWeight, ScalarValueType{}))
{
IndexType idx = neighborhood.GetIndex();
ContinuousIndex<double, ImageDimension> cdx;
for (unsigned int i = 0; i < ImageDimension; ++i)
{
cdx[i] = static_cast<double>(idx[i]) - offset[i];
}
typename ShapeFunctionType::PointType point;
this->GetFeatureImage()->TransformContinuousIndexToPhysicalPoint(cdx, point);
ScalarValueType shape_term =
m_ShapePriorWeight * (m_ShapeFunction->Evaluate(point) - neighborhood.GetCenterPixel());
value += shape_term;
// collect max change to be used for calculating the time step
auto * globalData = (ShapePriorGlobalDataStruct *)gd;
globalData->m_MaxShapePriorChange = std::max(globalData->m_MaxShapePriorChange, itk::Math::abs(shape_term));
}
return value;
}
template <typename TImageType, typename TFeatureImageType>
auto
ShapePriorSegmentationLevelSetFunction<TImageType, TFeatureImageType>::ComputeGlobalTimeStep(void * gd) const
-> TimeStepType
{
TimeStepType dt;
auto * d = (ShapePriorGlobalDataStruct *)gd;
d->m_MaxAdvectionChange += d->m_MaxPropagationChange + d->m_MaxShapePriorChange;
if (itk::Math::abs(d->m_MaxCurvatureChange) > 0.0)
{
if (d->m_MaxAdvectionChange > 0.0)
{
dt = std::min((this->m_WaveDT / d->m_MaxAdvectionChange), (this->m_DT / d->m_MaxCurvatureChange));
}
else
{
dt = this->m_DT / d->m_MaxCurvatureChange;
}
}
else
{
if (d->m_MaxAdvectionChange > 0.0)
{
dt = this->m_WaveDT / d->m_MaxAdvectionChange;
}
else
{
dt = 0.0;
}
}
double maxScaleCoefficient = 0.0;
for (unsigned int i = 0; i < ImageDimension; ++i)
{
maxScaleCoefficient = std::max(this->m_ScaleCoefficients[i], maxScaleCoefficient);
}
dt /= maxScaleCoefficient;
// reset the values
d->m_MaxAdvectionChange = 0;
d->m_MaxPropagationChange = 0;
d->m_MaxCurvatureChange = 0;
d->m_MaxShapePriorChange = 0;
return dt;
}
} // end namespace itk
#endif
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