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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkLabelImageGaussianInterpolateImageFunction.hxx,v $
Language: C++
Date: $Date: $
Version: $Revision: $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or https://www.itk.org/HTML/Copyright.htm for details.
Portions of this code are covered under the VTK copyright.
See VTKCopyright.txt or http://www.kitware.com/VTKCopyright.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 itkLabelImageGaussianInterpolateImageFunction_hxx
#define itkLabelImageGaussianInterpolateImageFunction_hxx
#include "itkLabelImageGaussianInterpolateImageFunction.h"
namespace itk
{
/**
* Constructor
*/
template<typename TInputImage, typename TCoordRep, typename TPixelCompare>
LabelImageGaussianInterpolateImageFunction<TInputImage, TCoordRep, TPixelCompare>
::LabelImageGaussianInterpolateImageFunction()
{
}
template<typename TInputImage, typename TCoordRep, typename TPixelCompare>
typename LabelImageGaussianInterpolateImageFunction<TInputImage, TCoordRep, TPixelCompare>
::OutputType
LabelImageGaussianInterpolateImageFunction<TInputImage, TCoordRep, TPixelCompare>
::EvaluateAtContinuousIndex( const ContinuousIndexType & cindex, OutputType * itkNotUsed( grad ) ) const
{
vnl_vector<RealType> erfArray[ImageDimension];
vnl_vector<RealType> gerfArray[ImageDimension];
// Compute the ERF difference arrays
for( unsigned int d = 0; d < ImageDimension; d++ )
{
const bool evaluateGradient = false;
this->ComputeErrorFunctionArray( d, cindex[d], erfArray[d],
gerfArray[d], evaluateGradient );
}
// Loop over the voxels in the region identified
ImageRegion<ImageDimension> region;
for( unsigned int d = 0; d < ImageDimension; d++ )
{
const int boundingBoxSize = static_cast<int>(
this->m_BoundingBoxEnd[d] - this->m_BoundingBoxStart[d] + 0.5 );
const int begin = std::max( 0, static_cast<int>( std::floor( cindex[d] -
this->m_BoundingBoxStart[d] - this->m_CutoffDistance[d] ) ) );
const int end = std::min( boundingBoxSize, static_cast<int>( std::ceil(
cindex[d] - this->m_BoundingBoxStart[d] + this->m_CutoffDistance[d] ) ) );
region.SetIndex( d, begin );
region.SetSize( d, end - begin );
}
RealType wmax = 0.0;
OutputType Vmax = NumericTraits<OutputType>::ZeroValue();
// Create a map object to store weights for each label encountered
// inside the search region. This is not as efficient as having a
// linear list of labels, but probably not a huge deal compared to
// having to evaluate the erf function
typedef std::map<OutputType, RealType, TPixelCompare> WeightMapType;
typedef typename std::map<OutputType, RealType, TPixelCompare>::iterator WeightMapIteratorType;
WeightMapType weightMap;
ImageRegionConstIteratorWithIndex<InputImageType> It( this->GetInputImage(), region );
for( It.GoToBegin(); !It.IsAtEnd(); ++It )
{
unsigned int j = It.GetIndex()[0];
RealType w = erfArray[0][j];
for( unsigned int d = 1; d < ImageDimension; d++)
{
j = It.GetIndex()[d];
w *= erfArray[d][j];
}
const OutputType V = It.Get();
WeightMapIteratorType it = weightMap.find( V );
RealType wtest = 0.0;
if( it != weightMap.end() )
{
it->second += w;
wtest = it->second;
}
else
{
weightMap.insert( std::make_pair( V, w ) );
wtest = w;
}
//Keep track of the max value
if( wtest > wmax )
{
wmax = wtest;
Vmax = V;
}
}
return Vmax;
}
} // namespace itk
#endif
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