/usr/include/ITK-4.5/itkMeanSquaresImageToImageMetric.hxx is in libinsighttoolkit4-dev 4.5.0-3.
This file is owned by root:root, with mode 0o644.
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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.
*
*=========================================================================*/
#ifndef __itkMeanSquaresImageToImageMetric_hxx
#define __itkMeanSquaresImageToImageMetric_hxx
#include "itkMeanSquaresImageToImageMetric.h"
#include "itkCovariantVector.h"
#include "itkImageRandomConstIteratorWithIndex.h"
#include "itkImageRegionIterator.h"
#include "itkImageIterator.h"
#include "vnl/vnl_math.h"
namespace itk
{
/**
* Constructor
*/
template <typename TFixedImage, typename TMovingImage>
MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::MeanSquaresImageToImageMetric()
{
this->SetComputeGradient(true);
m_PerThread = NULL;
this->m_WithinThreadPreProcess = false;
this->m_WithinThreadPostProcess = false;
// For backward compatibility, the default behavior is to use all the pixels
// in the fixed image.
// This should be fixed in ITKv4 so that this metric behaves as the others.
this->SetUseAllPixels(true);
}
template <typename TFixedImage, typename TMovingImage>
MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::~MeanSquaresImageToImageMetric()
{
delete[] m_PerThread;
m_PerThread = NULL;
}
/**
* Print out internal information about this class
*/
template <typename TFixedImage, typename TMovingImage>
void
MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
}
/**
* Initialize
*/
template <typename TFixedImage, typename TMovingImage>
void
MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::Initialize(void)
throw ( ExceptionObject )
{
this->Superclass::Initialize();
this->Superclass::MultiThreadingInitialize();
delete[] m_PerThread;
m_PerThread = new AlignedPerThreadType[this->m_NumberOfThreads];
for( ThreadIdType threadID = 0; threadID < this->m_NumberOfThreads; threadID++ )
{
m_PerThread[threadID].m_MSEDerivative.SetSize(this->m_NumberOfParameters);
}
}
template <typename TFixedImage, typename TMovingImage>
inline bool
MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::GetValueThreadProcessSample(ThreadIdType threadID,
SizeValueType fixedImageSample,
const MovingImagePointType & itkNotUsed(mappedPoint),
double movingImageValue) const
{
double diff = movingImageValue - this->m_FixedImageSamples[fixedImageSample].value;
m_PerThread[threadID].m_MSE += diff * diff;
return true;
}
template <typename TFixedImage, typename TMovingImage>
typename MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::MeasureType
MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::GetValue(const ParametersType & parameters) const
{
itkDebugMacro("GetValue( " << parameters << " ) ");
if( !this->m_FixedImage )
{
itkExceptionMacro(<< "Fixed image has not been assigned");
}
for( unsigned int i = 0; i < this->m_NumberOfThreads; ++i )
{
m_PerThread[i].m_MSE = NumericTraits<MeasureType>::ZeroValue();
}
// Set up the parameters in the transform
this->m_Transform->SetParameters(parameters);
// MUST BE CALLED TO INITIATE PROCESSING
this->GetValueMultiThreadedInitiate();
itkDebugMacro("Ratio of voxels mapping into moving image buffer: "
<< this->m_NumberOfPixelsCounted << " / "
<< this->m_NumberOfFixedImageSamples
<< std::endl);
if( this->m_NumberOfPixelsCounted <
this->m_NumberOfFixedImageSamples / 4 )
{
itkExceptionMacro("Too many samples map outside moving image buffer: "
<< this->m_NumberOfPixelsCounted << " / "
<< this->m_NumberOfFixedImageSamples
<< std::endl);
}
double mse = m_PerThread[0].m_MSE;
for( unsigned int t = 1; t < this->m_NumberOfThreads; t++ )
{
mse += m_PerThread[t].m_MSE;
}
mse /= this->m_NumberOfPixelsCounted;
return mse;
}
template <typename TFixedImage, typename TMovingImage>
inline bool
MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::GetValueAndDerivativeThreadProcessSample(ThreadIdType threadID,
SizeValueType fixedImageSample,
const MovingImagePointType & itkNotUsed(mappedPoint),
double movingImageValue,
const ImageDerivativesType &
movingImageGradientValue) const
{
double diff = movingImageValue - this->m_FixedImageSamples[fixedImageSample].value;
AlignedPerThreadType &threadS = m_PerThread[threadID];
threadS.m_MSE += diff * diff;
FixedImagePointType fixedImagePoint = this->m_FixedImageSamples[fixedImageSample].point;
// Need to use one of the threader transforms if we're
// not in thread 0.
//
// Use a raw pointer here to avoid the overhead of smart pointers.
// For instance, Register and UnRegister have mutex locks around
// the reference counts.
TransformType *transform;
if( threadID > 0 )
{
transform = this->m_ThreaderTransform[threadID - 1];
}
else
{
transform = this->m_Transform;
}
// Jacobian should be evaluated at the unmapped (fixed image) point.
transform->ComputeJacobianWithRespectToParameters(fixedImagePoint,threadS.m_Jacobian);
for( unsigned int par = 0; par < this->m_NumberOfParameters; par++ )
{
double sum = 0.0;
for( unsigned int dim = 0; dim < MovingImageDimension; dim++ )
{
sum += 2.0 *diff *threadS.m_Jacobian(dim, par) * movingImageGradientValue[dim];
}
threadS.m_MSEDerivative[par] += sum;
}
return true;
}
/**
* Get the both Value and Derivative Measure
*/
template <typename TFixedImage, typename TMovingImage>
void
MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::GetValueAndDerivative(const ParametersType & parameters,
MeasureType & value,
DerivativeType & derivative) const
{
if( !this->m_FixedImage )
{
itkExceptionMacro(<< "Fixed image has not been assigned");
}
// Set up the parameters in the transform
this->m_Transform->SetParameters(parameters);
// Reset the joint pdfs to zero
for( unsigned int i = 0; i < this->m_NumberOfThreads; ++i )
{
m_PerThread[i].m_MSE = NumericTraits<MeasureType>::ZeroValue();
}
// Set output values to zero
if( derivative.GetSize() != this->m_NumberOfParameters )
{
derivative = DerivativeType(this->m_NumberOfParameters);
}
memset( derivative.data_block(),
0,
this->m_NumberOfParameters * sizeof( double ) );
for( ThreadIdType threadID = 0; threadID < this->m_NumberOfThreads; threadID++ )
{
memset( m_PerThread[threadID].m_MSEDerivative.data_block(),
0,
this->m_NumberOfParameters * sizeof( double ) );
}
// MUST BE CALLED TO INITIATE PROCESSING
this->GetValueAndDerivativeMultiThreadedInitiate();
itkDebugMacro("Ratio of voxels mapping into moving image buffer: "
<< this->m_NumberOfPixelsCounted << " / "
<< this->m_NumberOfFixedImageSamples
<< std::endl);
if( this->m_NumberOfPixelsCounted <
this->m_NumberOfFixedImageSamples / 4 )
{
itkExceptionMacro("Too many samples map outside moving image buffer: "
<< this->m_NumberOfPixelsCounted << " / "
<< this->m_NumberOfFixedImageSamples
<< std::endl);
}
value = 0;
for( unsigned int t = 0; t < this->m_NumberOfThreads; t++ )
{
value += m_PerThread[t].m_MSE;
for( unsigned int parameter = 0; parameter < this->m_NumberOfParameters;
parameter++ )
{
derivative[parameter] += m_PerThread[t].m_MSEDerivative[parameter];
}
}
value /= this->m_NumberOfPixelsCounted;
for( unsigned int parameter = 0; parameter < this->m_NumberOfParameters;
parameter++ )
{
derivative[parameter] /= this->m_NumberOfPixelsCounted;
}
}
/**
* Get the match measure derivative
*/
template <typename TFixedImage, typename TMovingImage>
void
MeanSquaresImageToImageMetric<TFixedImage, TMovingImage>
::GetDerivative(const ParametersType & parameters,
DerivativeType & derivative) const
{
if( !this->m_FixedImage )
{
itkExceptionMacro(<< "Fixed image has not been assigned");
}
MeasureType value;
// call the combined version
this->GetValueAndDerivative(parameters, value, derivative);
}
} // end namespace itk
#endif
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