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itkDanielssonDistanceMapImageFilter.hxx
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itkDanielssonDistanceMapImageFilter.hxx
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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 itkDanielssonDistanceMapImageFilter_hxx
#define itkDanielssonDistanceMapImageFilter_hxx
#include <iostream>
#include "itkReflectiveImageRegionConstIterator.h"
#include "itkImageRegionConstIteratorWithIndex.h"
#include <algorithm> // For max.
namespace itk
{
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::DanielssonDistanceMapImageFilter()
{
this->SetNumberOfRequiredOutputs(3);
// distance map
this->SetNthOutput(0, this->MakeOutput(0));
// voronoi map
this->SetNthOutput(1, this->MakeOutput(1));
// distance vectors
this->SetNthOutput(2, this->MakeOutput(2));
m_SquaredDistance = false;
m_InputIsBinary = false;
}
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
auto
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::MakeOutput(
DataObjectPointerArraySizeType idx) -> DataObjectPointer
{
if (idx == 1)
{
return VoronoiImageType::New().GetPointer();
}
else
{
if (idx == 2)
{
return VectorImageType::New().GetPointer();
}
}
return Superclass::MakeOutput(idx);
}
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
auto
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::GetDistanceMap() -> OutputImageType *
{
return dynamic_cast<OutputImageType *>(this->ProcessObject::GetOutput(0));
}
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
auto
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::GetVoronoiMap() -> VoronoiImageType *
{
return dynamic_cast<VoronoiImageType *>(this->ProcessObject::GetOutput(1));
}
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
auto
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::GetVectorDistanceMap() -> VectorImageType *
{
return dynamic_cast<VectorImageType *>(this->ProcessObject::GetOutput(2));
}
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
void
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::PrepareData()
{
itkDebugMacro("PrepareData Start");
VoronoiImagePointer voronoiMap = this->GetVoronoiMap();
InputImagePointer inputImage = dynamic_cast<const InputImageType *>(ProcessObject::GetInput(0));
voronoiMap->SetLargestPossibleRegion(inputImage->GetLargestPossibleRegion());
voronoiMap->SetBufferedRegion(inputImage->GetBufferedRegion());
voronoiMap->SetRequestedRegion(inputImage->GetRequestedRegion());
voronoiMap->Allocate();
OutputImagePointer distanceMap = this->GetDistanceMap();
distanceMap->SetLargestPossibleRegion(inputImage->GetLargestPossibleRegion());
distanceMap->SetBufferedRegion(inputImage->GetBufferedRegion());
distanceMap->SetRequestedRegion(inputImage->GetRequestedRegion());
distanceMap->Allocate();
typename OutputImageType::RegionType region = voronoiMap->GetRequestedRegion();
// find the largest of the image dimensions
SizeType size = region.GetSize();
SizeValueType maxLength = 0;
for (unsigned int dim = 0; dim < InputImageDimension; ++dim)
{
maxLength = std::max(maxLength, size[dim]);
}
ImageRegionConstIteratorWithIndex<InputImageType> it(inputImage, region);
ImageRegionIteratorWithIndex<VoronoiImageType> ot(voronoiMap, region);
itkDebugMacro("PrepareData: Copy input to output");
if (m_InputIsBinary)
{
VoronoiPixelType npt = 1;
while (!ot.IsAtEnd())
{
if (it.Get())
{
ot.Set(npt);
}
else
{
ot.Set(0);
}
++it;
++ot;
}
}
else
{
while (!ot.IsAtEnd())
{
ot.Set(static_cast<VoronoiPixelType>(it.Get()));
++it;
++ot;
}
}
VectorImagePointer distanceComponents = GetVectorDistanceMap();
distanceComponents->SetLargestPossibleRegion(inputImage->GetLargestPossibleRegion());
distanceComponents->SetBufferedRegion(inputImage->GetBufferedRegion());
distanceComponents->SetRequestedRegion(inputImage->GetRequestedRegion());
distanceComponents->Allocate();
ImageRegionIteratorWithIndex<VectorImageType> ct(distanceComponents, region);
OffsetType maxValue;
OffsetType minValue;
for (unsigned int j = 0; j < InputImageDimension; ++j)
{
maxValue[j] = 2 * maxLength;
minValue[j] = 0;
}
itkDebugMacro("PrepareData: Copy output to ct");
// Iterate over the input image and distanceComponents image.
// Wherever the input image is non-zero, initialize the distanceComponents image to the minValue.
// Wherever the input image is zero, initialize the distanceComponents image to the maxValue.
it.GoToBegin();
while (!it.IsAtEnd())
{
if (it.Get())
{
ct.Set(minValue);
}
else
{
ct.Set(maxValue);
}
++it;
++ct;
}
itkDebugMacro("PrepareData End");
}
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
void
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::ComputeVoronoiMap()
{
itkDebugMacro("ComputeVoronoiMap Start");
VoronoiImagePointer voronoiMap = this->GetVoronoiMap();
OutputImagePointer distanceMap = this->GetDistanceMap();
VectorImagePointer distanceComponents = this->GetVectorDistanceMap();
typename OutputImageType::RegionType region = voronoiMap->GetRequestedRegion();
ImageRegionIteratorWithIndex<VoronoiImageType> ot(voronoiMap, region);
ImageRegionIteratorWithIndex<VectorImageType> ct(distanceComponents, region);
ImageRegionIteratorWithIndex<OutputImageType> dt(distanceMap, region);
itkDebugMacro("ComputeVoronoiMap Region: " << region);
while (!ot.IsAtEnd())
{
IndexType index = ct.GetIndex() + ct.Get();
if (region.IsInside(index))
{
ot.Set(voronoiMap->GetPixel(index));
}
OffsetType distanceVector = ct.Get();
double distance = 0.0;
if (m_UseImageSpacing)
{
for (unsigned int i = 0; i < InputImageDimension; ++i)
{
double component = distanceVector[i] * static_cast<double>(m_InputSpacingCache[i]);
distance += component * component;
}
}
else
{
for (unsigned int i = 0; i < InputImageDimension; ++i)
{
distance += distanceVector[i] * distanceVector[i];
}
}
if (m_SquaredDistance)
{
dt.Set(static_cast<OutputPixelType>(distance));
}
else
{
dt.Set(static_cast<OutputPixelType>(std::sqrt(distance)));
}
++ot;
++ct;
++dt;
}
itkDebugMacro("ComputeVoronoiMap End");
}
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
void
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::UpdateLocalDistance(
VectorImageType * components,
const IndexType & here,
const OffsetType & offset)
{
IndexType there = here + offset;
OffsetType offsetValueHere = components->GetPixel(here);
OffsetType offsetValueThere = components->GetPixel(there) + offset;
double norm1 = 0.0;
double norm2 = 0.0;
for (unsigned int i = 0; i < InputImageDimension; ++i)
{
auto v1 = static_cast<double>(offsetValueHere[i]);
auto v2 = static_cast<double>(offsetValueThere[i]);
if (m_UseImageSpacing)
{
auto spacingComponent = static_cast<double>(m_InputSpacingCache[i]);
v1 *= spacingComponent;
v2 *= spacingComponent;
}
norm1 += v1 * v1;
norm2 += v2 * v2;
}
if (norm1 > norm2)
{
components->SetPixel(here, offsetValueThere);
}
}
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
void
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::GenerateData()
{
this->PrepareData();
this->m_InputSpacingCache = this->GetInput()->GetSpacing();
// Specify images and regions.
VoronoiImagePointer voronoiMap = this->GetVoronoiMap();
VectorImagePointer distanceComponents = this->GetVectorDistanceMap();
RegionType region = voronoiMap->GetRequestedRegion();
itkDebugMacro("Region to process: " << region);
// Instantiate reflective iterator
ReflectiveImageRegionConstIterator<VectorImageType> it(distanceComponents, region);
typename VectorImageType::OffsetType voffset;
for (unsigned int dim = 0; dim < InputImageDimension; ++dim)
{
if (region.GetSize()[dim] > 1)
{
voffset[dim] = 1;
}
else
{
voffset[dim] = 0;
}
}
it.SetBeginOffset(voffset);
it.SetEndOffset(voffset);
it.GoToBegin();
// Set up an iterator for the input image.
// In this image, non-zero values are the background and zero values are the foreground.
// The foreground values are where the distance map should be solved.
// We iterate over this input image so that all background (non-zero) values are ignored in the
// distance map computation.
InputImagePointer inputImage = dynamic_cast<const InputImageType *>(ProcessObject::GetInput(0));
ReflectiveImageRegionConstIterator<const InputImageType> inputIt(inputImage, region);
inputIt.SetBeginOffset(voffset);
inputIt.SetEndOffset(voffset);
inputIt.GoToBegin();
// Support progress methods/callbacks.
// Each pixel is visited 2^InputImageDimension times, and the number
// of visits per pixel needs to be computed for progress reporting.
SizeValueType visitsPerPixel = (1 << InputImageDimension);
SizeValueType updateVisits = region.GetNumberOfPixels() * visitsPerPixel / 10;
if (updateVisits < 1)
{
updateVisits = 1;
}
const float updatePeriod = static_cast<float>(updateVisits) * 10.0;
// Process image.
OffsetType offset;
offset.Fill(0);
SizeValueType i = 0;
itkDebugMacro("GenerateData: Computing distance transform");
while (!it.IsAtEnd())
{
if (!(i % updateVisits))
{
this->UpdateProgress(static_cast<float>(i) / updatePeriod);
}
// The background is the region from which we are growing.
// The region we want to solve for is the foreground.
// The background pixels are set to a non-zero value.
// We can ignore these pixels in the update step.
if (!inputIt.Get())
{
IndexType here = it.GetIndex();
for (unsigned int dim = 0; dim < InputImageDimension; ++dim)
{
if (region.GetSize()[dim] <= 1)
{
continue;
}
if (it.IsReflected(dim))
{
offset[dim]++;
UpdateLocalDistance(distanceComponents, here, offset);
offset[dim] = 0;
}
else
{
offset[dim]--;
UpdateLocalDistance(distanceComponents, here, offset);
offset[dim] = 0;
}
}
}
++it;
++i;
++inputIt;
}
itkDebugMacro("GenerateData: ComputeVoronoiMap");
this->ComputeVoronoiMap();
}
template <typename TInputImage, typename TOutputImage, typename TVoronoiImage>
void
DanielssonDistanceMapImageFilter<TInputImage, TOutputImage, TVoronoiImage>::PrintSelf(std::ostream & os,
Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Danielson Distance: " << std::endl;
os << indent << "Input Is Binary : " << m_InputIsBinary << std::endl;
os << indent << "Use Image Spacing : " << m_UseImageSpacing << std::endl;
os << indent << "Squared Distance : " << m_SquaredDistance << std::endl;
}
} // end namespace itk
#endif