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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* 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
*
* http://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.
*
*=========================================================================*/
/*=========================================================================
*
* Portions of this file are subject to the VTK Toolkit Version 3 copyright.
*
* Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
*
* For complete copyright, license and disclaimer of warranty information
* please refer to the NOTICE file at the top of the ITK source tree.
*
*=========================================================================*/
#ifndef itkLabelImageGaussianInterpolateImageFunction_hxx
#define itkLabelImageGaussianInterpolateImageFunction_hxx
#include "itkLabelImageGaussianInterpolateImageFunction.h"
namespace itk
{
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->GetBoundingBoxEnd()[d] - this->GetBoundingBoxStart()[d] + 0.5 );
const int begin = std::max( 0, static_cast<int>( std::floor( cindex[d] -
this->GetBoundingBoxStart()[d] - this->GetCutOffDistance()[d] ) ) );
const int end = std::min( boundingBoxSize, static_cast<int>( std::ceil(
cindex[d] - this->GetBoundingBoxStart()[d] + this->GetCutOffDistance()[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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