/usr/include/ITK-4.5/itkMattesMutualInformationImageToImageMetric.hxx is in libinsighttoolkit4-dev 4.5.0-3.
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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 __itkMattesMutualInformationImageToImageMetric_hxx
#define __itkMattesMutualInformationImageToImageMetric_hxx
#include "itkMattesMutualInformationImageToImageMetric.h"
#include "itkImageRandomConstIteratorWithIndex.h"
#include "itkImageRegionIterator.h"
#include "itkImageIterator.h"
#include "vnl/vnl_math.h"
#include "itkStatisticsImageFilter.h"
#include "vnl/vnl_vector.h"
#include "vnl/vnl_c_vector.h"
namespace itk
{
/**
* Constructor
*/
template <typename TFixedImage, typename TMovingImage>
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::MattesMutualInformationImageToImageMetric() :
m_NumberOfHistogramBins(50),
m_MovingImageNormalizedMin(0.0),
m_FixedImageNormalizedMin(0.0),
m_MovingImageTrueMin(0.0),
m_MovingImageTrueMax(0.0),
m_FixedImageBinSize(0.0),
m_MovingImageBinSize(0.0),
m_CubicBSplineKernel(NULL),
m_CubicBSplineDerivativeKernel(NULL),
m_PRatioArray(0,0),
// Initialize memory
m_MovingImageMarginalPDF(0),
m_MMIMetricPerThreadVariables(NULL),
m_UseExplicitPDFDerivatives(true),
m_ImplicitDerivativesSecondPass(false)
{
this->SetComputeGradient(false); // don't use the default gradient for now
this->m_WithinThreadPreProcess = true;
this->m_WithinThreadPostProcess = false;
this->m_ComputeGradient = false;
}
template <typename TFixedImage, typename TMovingImage>
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::~MattesMutualInformationImageToImageMetric()
{
delete[] this->m_MMIMetricPerThreadVariables;
}
template <typename TFixedImage, typename TMovingImage>
void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "NumberOfHistogramBins: ";
os << this->m_NumberOfHistogramBins << std::endl;
// Debugging information
os << indent << "FixedImageNormalizedMin: ";
os << this->m_FixedImageNormalizedMin << std::endl;
os << indent << "MovingImageNormalizedMin: ";
os << this->m_MovingImageNormalizedMin << std::endl;
os << indent << "MovingImageTrueMin: ";
os << this->m_MovingImageTrueMin << std::endl;
os << indent << "MovingImageTrueMax: ";
os << this->m_MovingImageTrueMax << std::endl;
os << indent << "FixedImageBinSize: ";
os << this->m_FixedImageBinSize << std::endl;
os << indent << "MovingImageBinSize: ";
os << this->m_MovingImageBinSize << std::endl;
os << indent << "UseExplicitPDFDerivatives: ";
os << this->m_UseExplicitPDFDerivatives << std::endl;
os << indent << "ImplicitDerivativesSecondPass: ";
os << this->m_ImplicitDerivativesSecondPass << std::endl;
if( this->m_MMIMetricPerThreadVariables && this->m_MMIMetricPerThreadVariables[0].JointPDF.IsNotNull() )
{
os << indent << "JointPDF: ";
os << this->m_MMIMetricPerThreadVariables[0].JointPDF << std::endl;
}
if( this->m_MMIMetricPerThreadVariables && this->m_MMIMetricPerThreadVariables[0].JointPDFDerivatives.IsNotNull() )
{
os << indent << "JointPDFDerivatives: ";
os << this->m_MMIMetricPerThreadVariables[0].JointPDFDerivatives;
}
}
template <typename TFixedImage, typename TMovingImage>
void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::Initialize(void)
throw ( ExceptionObject )
{
this->Superclass::Initialize();
this->Superclass::MultiThreadingInitialize();
{
/**
* Compute the minimum and maximum within the specified mask
* region for creating the size of the 2D joint histogram.
* Areas outside the masked region should be ignored
* in computing the range of intensity values.
*/
this->m_FixedImageTrueMin = vcl_numeric_limits<typename TFixedImage::PixelType>::max();
this->m_FixedImageTrueMax = vcl_numeric_limits<typename TFixedImage::PixelType>::min();
this->m_MovingImageTrueMin = vcl_numeric_limits<typename TMovingImage::PixelType>::max();
this->m_MovingImageTrueMax = vcl_numeric_limits<typename TMovingImage::PixelType>::min();
// We need to make robust measures only over the requested mask region
itk::ImageRegionConstIteratorWithIndex<TFixedImage> fi(this->m_FixedImage, this->m_FixedImage->GetBufferedRegion() );
while( !fi.IsAtEnd() )
{
typename TFixedImage::PointType fixedSpacePhysicalPoint;
this->m_FixedImage->TransformIndexToPhysicalPoint(fi.GetIndex(), fixedSpacePhysicalPoint);
// A null mask implies entire space is to be used.
if( this->m_FixedImageMask.IsNull()
|| this->m_FixedImageMask->IsInside(fixedSpacePhysicalPoint)
)
{
const typename TFixedImage::PixelType currValue = fi.Get();
this->m_FixedImageTrueMin = (m_FixedImageTrueMin < currValue) ? this->m_FixedImageTrueMin : currValue;
this->m_FixedImageTrueMax = (m_FixedImageTrueMax > currValue) ? this->m_FixedImageTrueMax : currValue;
}
++fi;
}
{
itk::ImageRegionConstIteratorWithIndex<TMovingImage> mi(this->m_MovingImage,
this->m_MovingImage->GetBufferedRegion() );
while( !mi.IsAtEnd() )
{
typename TMovingImage::PointType movingSpacePhysicalPoint;
this->m_MovingImage->TransformIndexToPhysicalPoint(mi.GetIndex(), movingSpacePhysicalPoint);
// A null mask implies entire space is to be used.
if( this->m_MovingImageMask.IsNull()
|| this->m_MovingImageMask->IsInside(movingSpacePhysicalPoint)
)
{
const typename TMovingImage::PixelType currValue = mi.Get();
this->m_MovingImageTrueMin = (m_MovingImageTrueMin < currValue) ? this->m_MovingImageTrueMin : currValue;
this->m_MovingImageTrueMax = (m_MovingImageTrueMax > currValue) ? this->m_MovingImageTrueMax : currValue;
}
++mi;
}
}
itkDebugMacro(" FixedImageMin: " << this->m_FixedImageTrueMin
<< " FixedImageMax: " << this->m_FixedImageTrueMax << std::endl);
itkDebugMacro(" MovingImageMin: " << this->m_MovingImageTrueMin
<< " MovingImageMax: " << this->m_MovingImageTrueMax << std::endl);
}
/**
* Compute binsize for the histograms.
*
* The binsize for the image intensities needs to be adjusted so that
* we can avoid dealing with boundary conditions using the cubic
* spline as the Parzen window. We do this by increasing the size
* of the bins so that the joint histogram becomes "padded" at the
* borders. Because we are changing the binsize,
* we also need to shift the minimum by the padded amount in order to
* avoid minimum values filling in our padded region.
*
* Note that there can still be non-zero bin values in the padded region,
* it's just that these bins will never be a central bin for the Parzen
* window.
*
*/
const int padding = 2; // this will pad by 2 bins
this->m_FixedImageBinSize = ( this->m_FixedImageTrueMax - this->m_FixedImageTrueMin )
/ static_cast<PDFValueType>( this->m_NumberOfHistogramBins - 2 * padding );
this->m_FixedImageNormalizedMin = this->m_FixedImageTrueMin / this->m_FixedImageBinSize -
static_cast<PDFValueType>( padding );
this->m_MovingImageBinSize = ( this->m_MovingImageTrueMax - this->m_MovingImageTrueMin )
/ static_cast<PDFValueType>( this->m_NumberOfHistogramBins - 2 * padding );
this->m_MovingImageNormalizedMin = this->m_MovingImageTrueMin / this->m_MovingImageBinSize -
static_cast<PDFValueType>( padding );
itkDebugMacro("FixedImageNormalizedMin: " << this->m_FixedImageNormalizedMin);
itkDebugMacro("MovingImageNormalizedMin: " << this->m_MovingImageNormalizedMin);
itkDebugMacro("FixedImageBinSize: " << this->m_FixedImageBinSize);
itkDebugMacro("MovingImageBinSize; " << this->m_MovingImageBinSize);
/**
* Allocate memory for the marginal PDF and initialize values
* to zero. The marginal PDFs are stored as std::vector.
*/
this->m_MovingImageMarginalPDF.resize(m_NumberOfHistogramBins, 0.0F);
delete[] this->m_MMIMetricPerThreadVariables;
this->m_MMIMetricPerThreadVariables = new AlignedMMIMetricPerThreadStruct[ this->m_NumberOfThreads ];
{
const int binRange = this->m_NumberOfHistogramBins / this->m_NumberOfThreads;
for( ThreadIdType threadID = 0; threadID < this->m_NumberOfThreads; threadID++ )
{
this->m_MMIMetricPerThreadVariables[threadID].JointPDFStartBin = threadID * binRange;
this->m_MMIMetricPerThreadVariables[threadID].JointPDFEndBin = ( threadID + 1 ) * binRange - 1;
}
// Ensure that the last EndBin range contains the last histogram bin
this->m_MMIMetricPerThreadVariables[this->m_NumberOfThreads -
1].JointPDFStartBin = ( this->m_NumberOfThreads - 1 ) * binRange;
this->m_MMIMetricPerThreadVariables[this->m_NumberOfThreads - 1].JointPDFEndBin = this->m_NumberOfHistogramBins - 1;
}
{
JointPDFRegionType jointPDFRegion;
{
// For the joint PDF define a region starting from {0,0}
// with size {m_NumberOfHistogramBins, this->m_NumberOfHistogramBins}.
// The dimension represents fixed image bin size
// and moving image bin size , respectively.
JointPDFIndexType jointPDFIndex;
jointPDFIndex.Fill(0);
JointPDFSizeType jointPDFSize;
jointPDFSize.Fill(m_NumberOfHistogramBins);
jointPDFRegion.SetIndex(jointPDFIndex);
jointPDFRegion.SetSize(jointPDFSize);
}
// By setting these values, the joint histogram physical locations will
// correspond to intensity values.
typename JointPDFType::PointType origin;
origin[0] = this->m_FixedImageTrueMin;
origin[1] = this->m_MovingImageTrueMin;
typename JointPDFType::SpacingType spacing;
spacing[0] = this->m_FixedImageBinSize;
spacing[1] = this->m_MovingImageBinSize;
/**
* Allocate memory for the joint PDF and joint PDF derivatives.
* The joint PDF and joint PDF derivatives are store as itk::Image.
*/
for( ThreadIdType threadID = 0; threadID < this->m_NumberOfThreads; ++threadID )
{
this->m_MMIMetricPerThreadVariables[threadID].JointPDF = JointPDFType::New();
this->m_MMIMetricPerThreadVariables[threadID].JointPDF->SetRegions(jointPDFRegion);
this->m_MMIMetricPerThreadVariables[threadID].JointPDF->SetOrigin(origin);
this->m_MMIMetricPerThreadVariables[threadID].JointPDF->SetSpacing(spacing);
this->m_MMIMetricPerThreadVariables[threadID].JointPDF->Allocate();
}
}
//
// Now allocate memory according to the user-selected method.
//
if( this->m_UseExplicitPDFDerivatives )
{
// Deallocate the memory that may have been allocated for
// previous runs of the metric.
// and by allocating very small the static ones
// Not needed if this->m_UseExplicitPDFDerivatives
this->m_PRatioArray.SetSize(0, 0);
{
JointPDFDerivativesRegionType jointPDFDerivativesRegion;
{
// For the derivatives of the joint PDF define a region
// starting from {0,0,0} with size
// {m_NumberOfParameters,m_NumberOfHistogramBins,
// this->m_NumberOfHistogramBins}. The dimension represents
// transform parameters, fixed image parzen window index and
// moving image parzen window index, respectively.
JointPDFDerivativesIndexType jointPDFDerivativesIndex;
jointPDFDerivativesIndex.Fill(0);
JointPDFDerivativesSizeType jointPDFDerivativesSize;
jointPDFDerivativesSize[0] = this->m_NumberOfParameters;
jointPDFDerivativesSize[1] = this->m_NumberOfHistogramBins;
jointPDFDerivativesSize[2] = this->m_NumberOfHistogramBins;
jointPDFDerivativesRegion.SetIndex(jointPDFDerivativesIndex);
jointPDFDerivativesRegion.SetSize(jointPDFDerivativesSize);
}
// Set the regions and allocate
for( ThreadIdType threadID = 0; threadID < this->m_NumberOfThreads; threadID++ )
{
this->m_MMIMetricPerThreadVariables[threadID].JointPDFDerivatives = JointPDFDerivativesType::New();
this->m_MMIMetricPerThreadVariables[threadID].JointPDFDerivatives->SetRegions( jointPDFDerivativesRegion);
this->m_MMIMetricPerThreadVariables[threadID].JointPDFDerivatives->Allocate();
}
}
}
else
{
// Deallocate the memory that may have been allocated for
// previous runs of the metric.
for( ThreadIdType threadID = 0; threadID < this->m_NumberOfThreads; ++threadID )
{
// Not needed if this->m_UseExplicitPDFDerivatives=false
this->m_MMIMetricPerThreadVariables[threadID].JointPDFDerivatives = NULL;
}
/** Allocate memory for helper array that will contain the pRatios
* for each bin of the joint histogram. This is part of the effort
* for flattening the computation of the PDF Jacobians.
*/
this->m_PRatioArray.SetSize(this->m_NumberOfHistogramBins, this->m_NumberOfHistogramBins);
this->m_PRatioArray.Fill(0.0);
for( ThreadIdType threadID = 0; threadID < this->m_NumberOfThreads; threadID++ )
{
this->m_MMIMetricPerThreadVariables[threadID].MetricDerivative.SetSize( this->GetNumberOfParameters() );
this->m_MMIMetricPerThreadVariables[threadID].MetricDerivative.Fill(NumericTraits<MeasureType>::Zero);
}
}
/**
* Setup the kernels used for the Parzen windows.
*/
this->m_CubicBSplineKernel = CubicBSplineFunctionType::New();
this->m_CubicBSplineDerivativeKernel = CubicBSplineDerivativeFunctionType::New();
/**
* Pre-compute the fixed image parzen window index for
* each point of the fixed image sample points list.
*/
// NOTE: Need to have computed this->m_FisedImageBinSize here.
this->ComputeFixedImageParzenWindowIndices(this->m_FixedImageSamples);
}
/**
* From the pre-computed samples, now
* fill in the parzen window index locations
*/
template <typename TFixedImage, typename TMovingImage>
void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::ComputeFixedImageParzenWindowIndices( FixedImageSampleContainer & samples)
{
const typename FixedImageSampleContainer::const_iterator end = samples.end();
for( typename FixedImageSampleContainer::iterator iter = samples.begin();
iter != end; ++iter )
{
// Determine parzen window arguments (see eqn 6 of Mattes paper [2]).
const PDFValueType windowTerm = static_cast<PDFValueType>( ( *iter ).value )
/ this->m_FixedImageBinSize
- this->m_FixedImageNormalizedMin;
OffsetValueType pindex = static_cast<OffsetValueType>( windowTerm );
// Make sure the extreme values are in valid bins
if( pindex < 2 )
{
pindex = 2;
}
else
{
const OffsetValueType nindex =
static_cast<OffsetValueType>( this->m_NumberOfHistogramBins ) - 3;
if( pindex > nindex )
{
pindex = nindex;
}
}
( *iter ).valueIndex = pindex;
}
}
template <typename TFixedImage, typename TMovingImage>
inline void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::GetValueThreadPreProcess(ThreadIdType threadID,
bool withinSampleThread) const
{
this->Superclass::GetValueThreadPreProcess(threadID, withinSampleThread);
this->m_MMIMetricPerThreadVariables[threadID].JointPDF->FillBuffer(0.0F);
this->m_MMIMetricPerThreadVariables[threadID].FixedImageMarginalPDF = std::vector<PDFValueType>(
m_NumberOfHistogramBins, 0.0F);
}
template <typename TFixedImage, typename TMovingImage>
inline bool
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::GetValueThreadProcessSample(ThreadIdType threadID,
SizeValueType fixedImageSample,
const MovingImagePointType & itkNotUsed(mappedPoint),
double movingImageValue) const
{
/**
* Compute this sample's contribution to the marginal and
* joint distributions.
*
*/
if( movingImageValue < this->m_MovingImageTrueMin )
{
return false;
}
else if( movingImageValue > this->m_MovingImageTrueMax )
{
return false;
}
// Determine parzen window arguments (see eqn 6 of Mattes paper [2]).
const PDFValueType movingImageParzenWindowTerm = movingImageValue
/ this->m_MovingImageBinSize
- this->m_MovingImageNormalizedMin;
// Same as floor
OffsetValueType movingImageParzenWindowIndex =
static_cast<OffsetValueType>( movingImageParzenWindowTerm );
if( movingImageParzenWindowIndex < 2 )
{
movingImageParzenWindowIndex = 2;
}
else
{
const OffsetValueType nindex =
static_cast<OffsetValueType>( this->m_NumberOfHistogramBins ) - 3;
if( movingImageParzenWindowIndex > nindex )
{
movingImageParzenWindowIndex = nindex;
}
}
const unsigned int fixedImageParzenWindowIndex = this->m_FixedImageSamples[fixedImageSample].valueIndex;
this->m_MMIMetricPerThreadVariables[threadID].FixedImageMarginalPDF[fixedImageParzenWindowIndex] += 1;
// Pointer to affected bin to be updated
JointPDFValueType *pdfPtr = this->m_MMIMetricPerThreadVariables[threadID].JointPDF->GetBufferPointer()
+ ( fixedImageParzenWindowIndex * this->m_MMIMetricPerThreadVariables[threadID].JointPDF->GetOffsetTable()[1] );
// Move the pointer to the first affected bin
int pdfMovingIndex = static_cast<int>( movingImageParzenWindowIndex ) - 1;
pdfPtr += pdfMovingIndex;
const int pdfMovingIndexMax = static_cast<int>( movingImageParzenWindowIndex ) + 2;
PDFValueType movingImageParzenWindowArg = static_cast<PDFValueType>( pdfMovingIndex ) - movingImageParzenWindowTerm;
while( pdfMovingIndex <= pdfMovingIndexMax )
{
*( pdfPtr++ ) += static_cast<PDFValueType>( this->m_CubicBSplineKernel->Evaluate( movingImageParzenWindowArg) );
movingImageParzenWindowArg += 1;
++pdfMovingIndex;
}
return true;
}
template <typename TFixedImage, typename TMovingImage>
inline void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::GetValueThreadPostProcess( ThreadIdType threadID,
bool itkNotUsed(withinSampleThread) ) const
{
const int maxI = this->m_NumberOfHistogramBins
* ( this->m_MMIMetricPerThreadVariables[threadID].JointPDFEndBin-
this->m_MMIMetricPerThreadVariables[threadID].JointPDFStartBin + 1 );
const unsigned int tPdfPtrOffset =
( this->m_MMIMetricPerThreadVariables[threadID].JointPDFStartBin *
this->m_MMIMetricPerThreadVariables[0].JointPDF->GetOffsetTable()[1] );
JointPDFValueType * const pdfPtrStart = this->m_MMIMetricPerThreadVariables[0].JointPDF->GetBufferPointer() +
tPdfPtrOffset;
// The PDF domain is chunked based on thread. Each thread consolodates
// independent parts of the PDF.
for( unsigned int t = 1; t < this->m_NumberOfThreads; t++ )
{
JointPDFValueType * pdfPtr = pdfPtrStart;
JointPDFValueType const * tPdfPtr = this->m_MMIMetricPerThreadVariables[t].JointPDF->GetBufferPointer() +
tPdfPtrOffset;
JointPDFValueType const * const tPdfPtrEnd = tPdfPtr + maxI;
// for(i=0; i < maxI; i++)
while( tPdfPtr < tPdfPtrEnd )
{
*( pdfPtr++ ) += *( tPdfPtr++ );
}
}
for( int i = this->m_MMIMetricPerThreadVariables[threadID].JointPDFStartBin;
i <= this->m_MMIMetricPerThreadVariables[threadID].JointPDFEndBin; i++ )
{
PDFValueType PDFacc = this->m_MMIMetricPerThreadVariables[0].FixedImageMarginalPDF[i];
for( unsigned int t = 1; t < this->m_NumberOfThreads; t++ )
{
PDFacc += this->m_MMIMetricPerThreadVariables[t].FixedImageMarginalPDF[i];
}
this->m_MMIMetricPerThreadVariables[0].FixedImageMarginalPDF[i] = PDFacc;
}
// Sum of this threads domain into the
// this->m_MMIMetricPerThreadVariables[].JointPDFSum
// that covers that part of the domain.
this->m_MMIMetricPerThreadVariables[threadID].JointPDFSum = 0.0;
JointPDFValueType const * pdfPtr = pdfPtrStart;
for( int i = 0; i < maxI; i++ )
{
this->m_MMIMetricPerThreadVariables[threadID].JointPDFSum += *( pdfPtr++ );
}
}
template <typename TFixedImage, typename TMovingImage>
typename MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::MeasureType
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::GetValue(const ParametersType & parameters) const
{
// Set up the parameters in the transform
this->m_Transform->SetParameters(parameters);
// MUST BE CALLED TO INITIATE PROCESSING
this->GetValueMultiThreadedInitiate();
// MUST BE CALLED TO INITIATE PROCESSING
this->GetValueMultiThreadedPostProcessInitiate();
// Consolidate to the first element in the vector
for( ThreadIdType threadID = 1; threadID < this->m_NumberOfThreads; threadID++ )
{
this->m_MMIMetricPerThreadVariables[0].JointPDFSum += this->m_MMIMetricPerThreadVariables[threadID].JointPDFSum;
}
if( this->m_MMIMetricPerThreadVariables[0].JointPDFSum < itk::NumericTraits< PDFValueType >::epsilon() )
{
itkExceptionMacro("Joint PDF summed to zero\n" << this->m_MMIMetricPerThreadVariables[0].JointPDF );
}
std::fill(this->m_MovingImageMarginalPDF.begin(), this->m_MovingImageMarginalPDF.end(), 0.0F);
//NOTE: Since the m_ThreaderFixedImageMarginalPDF is the sum of mass
// in the fixed image dimension, accumulating these values gives the
// same answer as computing the the sum of individual values over
// the the entire histogram. IMPORTANT NOTICE: THIS MAKES AN
// ASSUMPTION OF CONSERVATION OF MASS OF THE BSPLINE SMOOTHING. The
// sum of all the values should equal the number of samples being
// used, since each sample contributes only one sample somewhere in
// the histogram
PDFValueType totalMassOfPDF = 0.0;
for( unsigned int i = 0; i < this->m_NumberOfHistogramBins; i++ )
{
totalMassOfPDF += this->m_MMIMetricPerThreadVariables[0].FixedImageMarginalPDF[i];
}
const PDFValueType normalizationFactor = 1.0 / this->m_MMIMetricPerThreadVariables[0].JointPDFSum;
JointPDFValueType *pdfPtr = this->m_MMIMetricPerThreadVariables[0].JointPDF->GetBufferPointer();
for( unsigned int i = 0; i < this->m_NumberOfHistogramBins; i++ )
{
PDFValueType * movingMarginalPtr = &(m_MovingImageMarginalPDF[0]);
for( unsigned int j = 0; j < this->m_NumberOfHistogramBins; j++ )
{
*( pdfPtr ) *= normalizationFactor;
*( movingMarginalPtr++ ) += *( pdfPtr++ );
}
}
if( this->m_NumberOfPixelsCounted < this->m_NumberOfFixedImageSamples / 16 )
{
itkExceptionMacro("Too many samples map outside moving image buffer: "
<< this->m_NumberOfPixelsCounted << " / "
<< this->m_NumberOfFixedImageSamples
<< std::endl);
}
// Normalize the fixed image marginal PDF
if( totalMassOfPDF == 0.0 )
{
itkExceptionMacro("Fixed image marginal PDF summed to zero");
}
for( unsigned int bin = 0; bin < this->m_NumberOfHistogramBins; bin++ )
{
this->m_MMIMetricPerThreadVariables[0].FixedImageMarginalPDF[bin] /= totalMassOfPDF;
}
/**
* Compute the metric by double sumdation over histogram.
*/
// Setup pointer to point to the first bin
JointPDFValueType *jointPDFPtr = this->m_MMIMetricPerThreadVariables[0].JointPDF->GetBufferPointer();
PDFValueType sum = 0.0;
for( unsigned int fixedIndex = 0;
fixedIndex < this->m_NumberOfHistogramBins;
++fixedIndex )
{
const PDFValueType fixedImagePDFValue = this->m_MMIMetricPerThreadVariables[0].FixedImageMarginalPDF[fixedIndex];
for( unsigned int movingIndex = 0;
movingIndex < this->m_NumberOfHistogramBins;
++movingIndex, jointPDFPtr++ )
{
const PDFValueType movingImagePDFValue = this->m_MovingImageMarginalPDF[movingIndex];
const PDFValueType jointPDFValue = *( jointPDFPtr );
// check for non-zero bin contribution
const PDFValueType closeToZero = vcl_numeric_limits<PDFValueType>::epsilon();
if( jointPDFValue > closeToZero && movingImagePDFValue > closeToZero )
{
const PDFValueType pRatio = vcl_log(jointPDFValue / movingImagePDFValue);
if( fixedImagePDFValue > closeToZero )
{
sum += jointPDFValue * ( pRatio - vcl_log(fixedImagePDFValue) );
}
} // end if-block to check non-zero bin contribution
} // end for-loop over moving index
} // end for-loop over fixed index
return static_cast<MeasureType>( -1.0 * sum );
}
template <typename TFixedImage, typename TMovingImage>
inline void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::GetValueAndDerivativeThreadPreProcess( ThreadIdType threadID,
bool itkNotUsed(withinSampleThread) ) const
{
this->m_MMIMetricPerThreadVariables[threadID].FixedImageMarginalPDF = std::vector<PDFValueType>(
m_NumberOfHistogramBins, 0.0F);
this->m_MMIMetricPerThreadVariables[threadID].JointPDF->FillBuffer(0.0F);
if( this->m_UseExplicitPDFDerivatives )
{
this->m_MMIMetricPerThreadVariables[threadID].JointPDFDerivatives->FillBuffer(0.0F);
}
}
template <typename TFixedImage, typename TMovingImage>
inline bool
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::GetValueAndDerivativeThreadProcessSample(ThreadIdType threadID,
SizeValueType fixedImageSample,
const MovingImagePointType & itkNotUsed(mappedPoint),
double movingImageValue,
const ImageDerivativesType &
movingImageGradientValue) const
{
/**
* Compute this sample's contribution to the marginal
* and joint distributions.
*
*/
if( movingImageValue < this->m_MovingImageTrueMin )
{
return false;
}
else if( movingImageValue > this->m_MovingImageTrueMax )
{
return false;
}
// Determine parzen window arguments (see eqn 6 of Mattes paper [2]).
PDFValueType movingImageParzenWindowTerm = movingImageValue / this->m_MovingImageBinSize -
this->m_MovingImageNormalizedMin;
OffsetValueType movingImageParzenWindowIndex = static_cast<OffsetValueType>( movingImageParzenWindowTerm );
// Make sure the extreme values are in valid bins
if( movingImageParzenWindowIndex < 2 )
{
movingImageParzenWindowIndex = 2;
}
else
{
const OffsetValueType nindex =
static_cast<OffsetValueType>( this->m_NumberOfHistogramBins ) - 3;
if( movingImageParzenWindowIndex > nindex )
{
movingImageParzenWindowIndex = nindex;
}
}
// Move the pointer to the fist affected bin
int pdfMovingIndex = static_cast<int>( movingImageParzenWindowIndex ) - 1;
const int pdfMovingIndexMax = static_cast<int>( movingImageParzenWindowIndex ) + 2;
const unsigned int fixedImageParzenWindowIndex = this->m_FixedImageSamples[fixedImageSample].valueIndex;
// Since a zero-order BSpline (box car) kernel is used for
// the fixed image marginal pdf, we need only increment the
// fixedImageParzenWindowIndex by value of 1.0.
this->m_MMIMetricPerThreadVariables[threadID].FixedImageMarginalPDF[fixedImageParzenWindowIndex] += 1;
/**
* The region of support of the parzen window determines which bins
* of the joint PDF are effected by the pair of image values.
* Since we are using a cubic spline for the moving image parzen
* window, four bins are effected. The fixed image parzen window is
* a zero-order spline (box car) and thus effects only one bin.
*
* The PDF is arranged so that moving image bins corresponds to the
* zero-th (column) dimension and the fixed image bins corresponds
* to the first (row) dimension.
*
*/
PDFValueType movingImageParzenWindowArg = static_cast<PDFValueType>( pdfMovingIndex ) -
static_cast<PDFValueType>( movingImageParzenWindowTerm );
// Pointer to affected bin to be updated
JointPDFValueType *pdfPtr = this->m_MMIMetricPerThreadVariables[threadID].JointPDF->GetBufferPointer()
+ ( fixedImageParzenWindowIndex * this->m_NumberOfHistogramBins )
+ pdfMovingIndex;
while( pdfMovingIndex <= pdfMovingIndexMax )
{
*( pdfPtr++ ) += static_cast<PDFValueType>( this->m_CubicBSplineKernel->Evaluate( movingImageParzenWindowArg) );
if( this->m_UseExplicitPDFDerivatives || this->m_ImplicitDerivativesSecondPass )
{
// Compute the cubicBSplineDerivative for later repeated use.
const PDFValueType cubicBSplineDerivativeValue = this->m_CubicBSplineDerivativeKernel->Evaluate(
movingImageParzenWindowArg);
// Compute PDF derivative contribution.
this->ComputePDFDerivatives(threadID,
fixedImageSample,
pdfMovingIndex,
movingImageGradientValue,
cubicBSplineDerivativeValue);
}
movingImageParzenWindowArg += 1.0;
++pdfMovingIndex;
}
return true;
}
template <typename TFixedImage, typename TMovingImage>
inline void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::GetValueAndDerivativeThreadPostProcess(ThreadIdType threadID,
bool withinSampleThread) const
{
this->GetValueThreadPostProcess(threadID, withinSampleThread);
if( this->m_UseExplicitPDFDerivatives )
{
const unsigned int rowSize = this->m_NumberOfParameters * this->m_NumberOfHistogramBins;
const unsigned int maxI =
rowSize * ( this->m_MMIMetricPerThreadVariables[threadID].JointPDFEndBin
- this->m_MMIMetricPerThreadVariables[threadID].JointPDFStartBin + 1 );
JointPDFDerivativesValueType *const pdfDPtrStart =
this->m_MMIMetricPerThreadVariables[0].JointPDFDerivatives->GetBufferPointer()
+ ( this->m_MMIMetricPerThreadVariables[threadID].JointPDFStartBin * rowSize );
const unsigned int tPdfDPtrOffset = this->m_MMIMetricPerThreadVariables[threadID].JointPDFStartBin * rowSize;
for( unsigned int t = 1; t < this->m_NumberOfThreads; t++ )
{
JointPDFDerivativesValueType * pdfDPtr = pdfDPtrStart;
JointPDFDerivativesValueType const *tPdfDPtr =
this->m_MMIMetricPerThreadVariables[t].JointPDFDerivatives->GetBufferPointer()
+ tPdfDPtrOffset;
JointPDFDerivativesValueType const * const tPdfDPtrEnd = tPdfDPtr + maxI;
// for(i = 0; i < maxI; i++)
while( tPdfDPtr < tPdfDPtrEnd )
{
*( pdfDPtr++ ) += *( tPdfDPtr++ );
}
}
const PDFValueType nFactor = 1.0 / ( this->m_MovingImageBinSize
* this->m_NumberOfPixelsCounted );
JointPDFDerivativesValueType * pdfDPtr = pdfDPtrStart;
JointPDFDerivativesValueType const * const tPdfDPtrEnd = pdfDPtrStart + maxI;
// for(int i = 0; i < maxI; i++)
while( pdfDPtr < tPdfDPtrEnd )
{
*( pdfDPtr++ ) *= nFactor;
}
}
}
/**
* Get the both Value and Derivative Measure
*/
template <typename TFixedImage, typename TMovingImage>
void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::GetValueAndDerivative(const ParametersType & parameters,
MeasureType & value,
DerivativeType & derivative) const
{
// Set output values to zero
value = NumericTraits<MeasureType>::Zero;
if( this->m_UseExplicitPDFDerivatives )
{
// 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( PDFValueType ) );
}
else
{
this->m_PRatioArray.Fill(0.0);
for( ThreadIdType threadID = 0; threadID < this->m_NumberOfThreads; threadID++ )
{
this->m_MMIMetricPerThreadVariables[threadID].MetricDerivative.Fill(NumericTraits<MeasureType>::Zero);
}
this->m_ImplicitDerivativesSecondPass = false;
}
// Set up the parameters in the transform
this->m_Transform->SetParameters(parameters);
// MUST BE CALLED TO INITIATE PROCESSING ON SAMPLES
this->GetValueAndDerivativeMultiThreadedInitiate();
// CALL IF DOING THREADED POST PROCESSING
this->GetValueAndDerivativeMultiThreadedPostProcessInitiate();
for( ThreadIdType threadID = 1; threadID < this->m_NumberOfThreads; threadID++ )
{
this->m_MMIMetricPerThreadVariables[0].JointPDFSum += this->m_MMIMetricPerThreadVariables[threadID].JointPDFSum;
}
if( this->m_MMIMetricPerThreadVariables[0].JointPDFSum < itk::NumericTraits< PDFValueType >::epsilon() )
{
itkExceptionMacro("Joint PDF summed to zero");
}
std::fill(this->m_MovingImageMarginalPDF.begin(), this->m_MovingImageMarginalPDF.end(), 0.0F);
PDFValueType totalMassOfPDF = 0.0;
for( unsigned int i = 0; i < this->m_NumberOfHistogramBins; i++ )
{
totalMassOfPDF += this->m_MMIMetricPerThreadVariables[0].FixedImageMarginalPDF[i];
}
const PDFValueType normalizationFactor = 1.0 / this->m_MMIMetricPerThreadVariables[0].JointPDFSum;
JointPDFValueType *pdfPtr = this->m_MMIMetricPerThreadVariables[0].JointPDF->GetBufferPointer();
for( unsigned int i = 0; i < this->m_NumberOfHistogramBins; i++ )
{
PDFValueType * movingMarginalPtr = &(m_MovingImageMarginalPDF[0]);
for( unsigned int j = 0; j < this->m_NumberOfHistogramBins; j++ )
{
*( pdfPtr ) *= normalizationFactor;
*( movingMarginalPtr++ ) += *( pdfPtr++ );
}
}
if( this->m_NumberOfPixelsCounted < this->m_NumberOfFixedImageSamples / 16 )
{
itkExceptionMacro("Too many samples map outside moving image buffer: "
<< this->m_NumberOfPixelsCounted << " / "
<< this->m_NumberOfFixedImageSamples
<< std::endl);
}
// Normalize the fixed image marginal PDF
if( totalMassOfPDF == 0.0 )
{
itkExceptionMacro("Fixed image marginal PDF summed to zero");
}
for( unsigned int bin = 0; bin < this->m_NumberOfHistogramBins; bin++ )
{
this->m_MMIMetricPerThreadVariables[0].FixedImageMarginalPDF[bin] /= totalMassOfPDF;
}
/**
* Compute the metric by double summation over histogram.
*/
// Setup pointer to point to the first bin
JointPDFValueType *jointPDFPtr = this->m_MMIMetricPerThreadVariables[0].JointPDF->GetBufferPointer();
// Initialize sum to zero
PDFValueType sum = 0.0;
const PDFValueType nFactor = 1.0 / ( this->m_MovingImageBinSize
* this->m_NumberOfPixelsCounted );
for( unsigned int fixedIndex = 0;
fixedIndex < this->m_NumberOfHistogramBins;
++fixedIndex )
{
const PDFValueType fixedImagePDFValue = this->m_MMIMetricPerThreadVariables[0].FixedImageMarginalPDF[fixedIndex];
for( unsigned int movingIndex = 0;
movingIndex < this->m_NumberOfHistogramBins;
++movingIndex, jointPDFPtr++ )
{
const PDFValueType movingImagePDFValue = this->m_MovingImageMarginalPDF[movingIndex];
const PDFValueType jointPDFValue = *( jointPDFPtr );
// check for non-zero bin contribution
const PDFValueType closeToZero = vcl_numeric_limits<PDFValueType>::epsilon();
if( jointPDFValue > closeToZero && movingImagePDFValue > closeToZero )
{
const PDFValueType pRatio = vcl_log(jointPDFValue / movingImagePDFValue);
if( fixedImagePDFValue > closeToZero )
{
sum += jointPDFValue * ( pRatio - vcl_log(fixedImagePDFValue) );
}
if( this->m_UseExplicitPDFDerivatives )
{
// move joint pdf derivative pointer to the right position
JointPDFValueType const * derivPtr =
this->m_MMIMetricPerThreadVariables[0].JointPDFDerivatives->GetBufferPointer()
+ ( fixedIndex * this->m_MMIMetricPerThreadVariables[0].JointPDFDerivatives->GetOffsetTable()[2] )
+ ( movingIndex * this->m_MMIMetricPerThreadVariables[0].JointPDFDerivatives->GetOffsetTable()[1] );
for( unsigned int parameter = 0; parameter < this->m_NumberOfParameters; ++parameter, derivPtr++ )
{
// Ref: eqn 23 of Thevenaz & Unser paper [3]
derivative[parameter] -= ( *derivPtr ) * pRatio;
} // end for-loop over parameters
}
else
{
this->m_PRatioArray[fixedIndex][movingIndex] = pRatio * nFactor;
}
} // end if-block to check non-zero bin contribution
} // end for-loop over moving index
} // end for-loop over fixed index
if( !( this->m_UseExplicitPDFDerivatives ) )
{
// Second pass: This one is done for accumulating the contributions
// to the derivative array.
//
this->m_ImplicitDerivativesSecondPass = true;
//
// MUST BE CALLED TO INITIATE PROCESSING ON SAMPLES
this->GetValueAndDerivativeMultiThreadedInitiate();
// CALL IF DOING THREADED POST PROCESSING
this->GetValueAndDerivativeMultiThreadedPostProcessInitiate();
// Consolidate the contributions from each one of the threads to the total
// derivative.
for( ThreadIdType threadId = 1; threadId < this->m_NumberOfThreads; ++threadId )
{
DerivativeType const * const source = &( this->m_MMIMetricPerThreadVariables[threadId].MetricDerivative );
for( unsigned int pp = 0; pp < this->m_NumberOfParameters; pp++ )
{
this->m_MMIMetricPerThreadVariables[0].MetricDerivative[pp] += ( *source )[pp];
}
}
derivative = this->m_MMIMetricPerThreadVariables[0].MetricDerivative;
}
value = static_cast<MeasureType>( -1.0 * sum );
}
/**
* Get the match measure derivative
*/
template <typename TFixedImage, typename TMovingImage>
void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::GetDerivative(const ParametersType & parameters,
DerivativeType & derivative) const
{
MeasureType value;
// call the combined version
this->GetValueAndDerivative(parameters, value, derivative);
}
/**
* Compute PDF derivatives contribution for each parameter
*/
template <typename TFixedImage, typename TMovingImage>
void
MattesMutualInformationImageToImageMetric<TFixedImage, TMovingImage>
::ComputePDFDerivatives(ThreadIdType threadID,
unsigned int sampleNumber,
int pdfMovingIndex,
const ImageDerivativesType & movingImageGradientValue,
PDFValueType cubicBSplineDerivativeValue) const
{
// Update bins in the PDF derivatives for the current intensity pair
// Could pre-compute
PDFValueType precomputedWeight = 0.0;
const int pdfFixedIndex = this->m_FixedImageSamples[sampleNumber].valueIndex;
JointPDFDerivativesValueType *derivPtr=0;
if( this->m_UseExplicitPDFDerivatives )
{
derivPtr = this->m_MMIMetricPerThreadVariables[threadID].JointPDFDerivatives->GetBufferPointer()
+ ( pdfFixedIndex * this->m_MMIMetricPerThreadVariables[threadID].JointPDFDerivatives->GetOffsetTable()[2] )
+ ( pdfMovingIndex * this->m_MMIMetricPerThreadVariables[threadID].JointPDFDerivatives->GetOffsetTable()[1] );
}
else
{
// Recover the precomputed weight for this specific PDF bin
precomputedWeight = this->m_PRatioArray[pdfFixedIndex][pdfMovingIndex];
}
if( !this->m_TransformIsBSpline )
{
/**
* Generic version which works for all transforms.
*/
// 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;
}
// Compute the transform Jacobian.
// Should pre-compute
typename TransformType::JacobianType &jacobian = this->m_MMIMetricPerThreadVariables[threadID].Jacobian;
transform->ComputeJacobianWithRespectToParameters( this->m_FixedImageSamples[sampleNumber].point, jacobian);
for( unsigned int mu = 0; mu < this->m_NumberOfParameters; mu++ )
{
PDFValueType innerProduct = 0.0;
for( unsigned int dim = 0; dim < Superclass::FixedImageDimension; dim++ )
{
innerProduct += jacobian[dim][mu] * movingImageGradientValue[dim];
}
const PDFValueType derivativeContribution = innerProduct * cubicBSplineDerivativeValue;
if( this->m_UseExplicitPDFDerivatives )
{
*( derivPtr ) -= derivativeContribution;
++derivPtr;
}
else
{
this->m_MMIMetricPerThreadVariables[threadID].MetricDerivative[mu] += precomputedWeight *
derivativeContribution;
}
}
}
else
{
const WeightsValueType *weights = NULL;
const IndexValueType * indices = NULL;
BSplineTransformWeightsType * weightsHelper = NULL;
BSplineTransformIndexArrayType *indicesHelper = NULL;
if( this->m_UseCachingOfBSplineWeights )
{
//
// If the transform is of type BSplineTransform, we can obtain
// a speed up by only processing the affected parameters. Note that
// these pointers are just pointing to pre-allocated rows of the caching
// arrays. There is therefore, no need to free this memory.
//
weights = this->m_BSplineTransformWeightsArray[sampleNumber];
indices = this->m_BSplineTransformIndicesArray[sampleNumber];
}
else
{
if( threadID > 0 )
{
weightsHelper = &( this->m_ThreaderBSplineTransformWeights[threadID - 1] );
indicesHelper = &( this->m_ThreaderBSplineTransformIndices[threadID - 1] );
}
else
{
weightsHelper = &( this->m_BSplineTransformWeights );
indicesHelper = &( this->m_BSplineTransformIndices );
}
// Get Jacobian at a point. A very specialized function just for BSplines
this->m_BSplineTransform->ComputeJacobianFromBSplineWeightsWithRespectToPosition(
this->m_FixedImageSamples[sampleNumber].point, *weightsHelper, *indicesHelper);
}
for( unsigned int dim = 0; dim < Superclass::FixedImageDimension; dim++ )
{
for( unsigned int mu = 0; mu < this->m_NumBSplineWeights; mu++ )
{
/* The array weights contains the Jacobian values in a 1-D array
* (because for each parameter the Jacobian is non-zero in only 1 of the
* possible dimensions) which is multiplied by the moving image
* gradient. */
PDFValueType innerProduct;
int parameterIndex;
if( this->m_UseCachingOfBSplineWeights )
{
innerProduct = movingImageGradientValue[dim] * weights[mu];
parameterIndex = indices[mu] + this->m_BSplineParametersOffset[dim];
}
else
{
innerProduct = movingImageGradientValue[dim] * ( *weightsHelper )[mu];
parameterIndex = ( *indicesHelper )[mu] + this->m_BSplineParametersOffset[dim];
}
const PDFValueType derivativeContribution = innerProduct * cubicBSplineDerivativeValue;
if( this->m_UseExplicitPDFDerivatives )
{
JointPDFValueType * const ptr = derivPtr + parameterIndex;
*( ptr ) -= derivativeContribution;
}
else
{
this->m_MMIMetricPerThreadVariables[threadID].MetricDerivative[parameterIndex] += precomputedWeight *
derivativeContribution;
}
} // end mu for loop
} // end dim for loop
} // end if-block transform is BSpline
}
} // end namespace itk
#endif
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