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itkImageToImageMetric.hxx
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itkImageToImageMetric.hxx
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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 itkImageToImageMetric_hxx
#define itkImageToImageMetric_hxx
#include "itkImageToImageMetric.h"
#include "itkImageRandomConstIteratorWithIndex.h"
#include "itkMath.h"
namespace itk
{
/**
* Constructor
*/
template< typename TFixedImage, typename TMovingImage >
ImageToImageMetric< TFixedImage, TMovingImage >
::ImageToImageMetric():
m_UseFixedImageIndexes(false),
m_FixedImageIndexes(0),
m_UseFixedImageSamplesIntensityThreshold(false),
m_FixedImageSamplesIntensityThreshold(0),
m_FixedImageSamples(0),
m_NumberOfParameters(0),
m_NumberOfFixedImageSamples(50000),
m_NumberOfPixelsCounted(0),
m_FixedImage(ITK_NULLPTR), // has to be provided by the user.
m_MovingImage(ITK_NULLPTR), // has to be provided by the user.
m_Transform(ITK_NULLPTR), // has to be provided by the user.
m_ThreaderTransform(ITK_NULLPTR), // constructed at initialization.
m_Interpolator(ITK_NULLPTR), // has to be provided by the user.
m_ComputeGradient(true), // metric computes gradient by default
m_GradientImage(ITK_NULLPTR), // computed at initialization
m_FixedImageMask(ITK_NULLPTR),
m_MovingImageMask(ITK_NULLPTR),
m_NumberOfThreads(1),
m_UseAllPixels(false),
m_UseSequentialSampling(false),
m_ReseedIterator(false),
m_RandomSeed(-1),
m_TransformIsBSpline(false),
m_NumBSplineWeights(0),
m_BSplineTransform(ITK_NULLPTR),
m_BSplineTransformWeightsArray(),
m_BSplineTransformIndicesArray(),
m_BSplinePreTransformPointsArray(0),
m_WithinBSplineSupportRegionArray(0),
m_BSplineParametersOffset(),
m_UseCachingOfBSplineWeights(true),
m_BSplineTransformWeights(),
m_BSplineTransformIndices(),
m_ThreaderBSplineTransformWeights(ITK_NULLPTR),
m_ThreaderBSplineTransformIndices(ITK_NULLPTR),
m_InterpolatorIsBSpline(false),
m_BSplineInterpolator(ITK_NULLPTR),
m_DerivativeCalculator(ITK_NULLPTR),
m_Threader(MultiThreaderType::New()),
m_ThreaderNumberOfMovingImageSamples(ITK_NULLPTR),
m_WithinThreadPreProcess(false),
m_WithinThreadPostProcess(false)
{
this->m_ThreaderParameter.metric = this;
this->m_NumberOfThreads = this->m_Threader->GetNumberOfThreads();
/* if 100% backward compatible, we should include this...but...
typename BSplineTransformType::Pointer transformer =
BSplineTransformType::New();
this->SetTransform (transformer);
typename BSplineInterpolatorType::Pointer interpolator =
BSplineInterpolatorType::New();
this->SetInterpolator (interpolator);
*/
}
template< typename TFixedImage, typename TMovingImage >
ImageToImageMetric< TFixedImage, TMovingImage >
::~ImageToImageMetric()
{
delete[] m_ThreaderNumberOfMovingImageSamples;
m_ThreaderNumberOfMovingImageSamples = ITK_NULLPTR;
delete[] m_ThreaderTransform;
m_ThreaderTransform = ITK_NULLPTR;
delete[] this->m_ThreaderBSplineTransformWeights;
this->m_ThreaderBSplineTransformWeights = ITK_NULLPTR;
delete[] this->m_ThreaderBSplineTransformIndices;
this->m_ThreaderBSplineTransformIndices = ITK_NULLPTR;
}
/**
* Set the number of threads. This will be clamped by the
* multithreader, so we must check to see if it is accepted.
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetNumberOfThreads(ThreadIdType numberOfThreads)
{
m_Threader->SetNumberOfThreads(numberOfThreads);
m_NumberOfThreads = m_Threader->GetNumberOfThreads();
}
/**
* Set the parameters that define a unique transform
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetTransformParameters(const ParametersType & parameters) const
{
if ( !m_Transform )
{
itkExceptionMacro(<< "Transform has not been assigned");
}
m_Transform->SetParameters(parameters);
}
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetNumberOfFixedImageSamples(SizeValueType numSamples)
{
if ( numSamples != m_NumberOfFixedImageSamples )
{
m_NumberOfFixedImageSamples = numSamples;
if ( m_NumberOfFixedImageSamples != this->m_FixedImageRegion.GetNumberOfPixels() )
{
this->SetUseAllPixels(false);
}
this->Modified();
}
}
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetFixedImageIndexes(const FixedImageIndexContainer & indexes)
{
this->SetUseFixedImageIndexes(true);
m_NumberOfFixedImageSamples = indexes.size();
m_FixedImageIndexes.resize(m_NumberOfFixedImageSamples);
for ( unsigned int i = 0; i < m_NumberOfFixedImageSamples; i++ )
{
m_FixedImageIndexes[i] = indexes[i];
}
}
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetUseFixedImageIndexes(bool useIndexes)
{
if ( useIndexes != m_UseFixedImageIndexes )
{
m_UseFixedImageIndexes = useIndexes;
if ( m_UseFixedImageIndexes )
{
this->SetUseAllPixels(false);
}
else
{
this->Modified();
}
}
}
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetFixedImageSamplesIntensityThreshold(const FixedImagePixelType & thresh)
{
if ( thresh != m_FixedImageSamplesIntensityThreshold )
{
m_FixedImageSamplesIntensityThreshold = thresh;
this->SetUseFixedImageSamplesIntensityThreshold(true);
this->Modified();
}
}
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetUseFixedImageSamplesIntensityThreshold(bool useThresh)
{
if ( useThresh != m_UseFixedImageSamplesIntensityThreshold )
{
m_UseFixedImageSamplesIntensityThreshold = useThresh;
if ( m_UseFixedImageSamplesIntensityThreshold )
{
this->SetUseAllPixels(false);
}
else
{
this->Modified();
}
}
}
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetFixedImageRegion(const FixedImageRegionType reg)
{
if ( reg != m_FixedImageRegion )
{
m_FixedImageRegion = reg;
if ( this->GetUseAllPixels() )
{
this->SetNumberOfFixedImageSamples( this->m_FixedImageRegion.GetNumberOfPixels() );
}
}
}
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetUseAllPixels(bool useAllPixels)
{
if ( useAllPixels != m_UseAllPixels )
{
m_UseAllPixels = useAllPixels;
if ( m_UseAllPixels )
{
this->SetUseFixedImageSamplesIntensityThreshold(false);
this->SetNumberOfFixedImageSamples( this->m_FixedImageRegion.GetNumberOfPixels() );
this->SetUseSequentialSampling(true);
}
else
{
this->SetUseSequentialSampling(false);
this->Modified();
}
}
}
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SetUseSequentialSampling(bool useSequential)
{
if ( useSequential != m_UseSequentialSampling )
{
m_UseSequentialSampling = useSequential;
if ( !m_UseSequentialSampling )
{
this->SetUseAllPixels(false);
}
else
{
this->Modified();
}
}
}
/**
* Initialize
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::Initialize(void)
throw ( ExceptionObject )
{
if ( !m_Transform )
{
itkExceptionMacro(<< "Transform is not present");
}
m_NumberOfParameters = m_Transform->GetNumberOfParameters();
if ( !m_Interpolator )
{
itkExceptionMacro(<< "Interpolator is not present");
}
if ( !m_MovingImage )
{
itkExceptionMacro(<< "MovingImage is not present");
}
if ( !m_FixedImage )
{
itkExceptionMacro(<< "FixedImage is not present");
}
// If the image is provided by a source, update the source.
if ( m_MovingImage->GetSource() )
{
m_MovingImage->GetSource()->Update();
}
// If the image is provided by a source, update the source.
if ( m_FixedImage->GetSource() )
{
m_FixedImage->GetSource()->Update();
}
//The use of FixedImageIndexes and the use of FixedImageRegion
//are mutually exclusive, so they should not both be checked.
if ( this->m_UseFixedImageIndexes == true )
{
if( this->m_FixedImageIndexes.size() == 0 )
{
itkExceptionMacro(<< "FixedImageIndexes list is empty");
}
}
else
{
// Make sure the FixedImageRegion is within the FixedImage buffered region
if ( m_FixedImageRegion.GetNumberOfPixels() == 0 )
{
itkExceptionMacro(<< "FixedImageRegion is empty");
}
if ( !m_FixedImageRegion.Crop( m_FixedImage->GetBufferedRegion() ) )
{
itkExceptionMacro(
<< "FixedImageRegion does not overlap the fixed image buffered region");
}
}
m_Interpolator->SetInputImage(m_MovingImage);
if ( m_ComputeGradient )
{
ComputeGradient();
}
// If there are any observers on the metric, call them to give the
// user code a chance to set parameters on the metric
this->InvokeEvent( InitializeEvent() );
}
/**
* MultiThreading Initialize
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::MultiThreadingInitialize(void)
throw ( ExceptionObject )
{
this->SetNumberOfThreads(m_NumberOfThreads);
delete[] m_ThreaderNumberOfMovingImageSamples;
m_ThreaderNumberOfMovingImageSamples = new unsigned int[m_NumberOfThreads - 1];
// Allocate the array of transform clones to be used in every thread
delete[] m_ThreaderTransform;
m_ThreaderTransform = new TransformPointer[m_NumberOfThreads - 1];
for ( ThreadIdType ithread = 0; ithread < m_NumberOfThreads - 1; ++ithread )
{
this->m_ThreaderTransform[ithread] = this->m_Transform->Clone();
}
m_FixedImageSamples.resize(m_NumberOfFixedImageSamples);
if ( m_UseSequentialSampling )
{
//
// Take all the pixels within the fixed image region)
// to create the sample points list.
//
SampleFullFixedImageRegion(m_FixedImageSamples);
}
else
{
if ( m_UseFixedImageIndexes )
{
//
// Use the list of indexes passed to the SetFixedImageIndexes
// member function .
//
SampleFixedImageIndexes(m_FixedImageSamples);
}
else
{
//
// Uniformly sample the fixed image (within the fixed image region)
// to create the sample points list.
//
SampleFixedImageRegion(m_FixedImageSamples);
}
}
//
// Check if the interpolator is of type BSplineInterpolateImageFunction.
// If so, we can make use of its EvaluateDerivatives method.
// Otherwise, we instantiate an external central difference
// derivative calculator.
//
m_InterpolatorIsBSpline = true;
BSplineInterpolatorType *testPtr = dynamic_cast< BSplineInterpolatorType * >(
this->m_Interpolator.GetPointer() );
if ( !testPtr )
{
m_InterpolatorIsBSpline = false;
m_DerivativeCalculator = DerivativeFunctionType::New();
m_DerivativeCalculator->UseImageDirectionOn();
m_DerivativeCalculator->SetInputImage(this->m_MovingImage);
m_BSplineInterpolator = ITK_NULLPTR;
itkDebugMacro("Interpolator is not BSpline");
}
else
{
m_BSplineInterpolator = testPtr;
m_BSplineInterpolator->SetNumberOfThreads(m_NumberOfThreads);
m_BSplineInterpolator->UseImageDirectionOn();
m_DerivativeCalculator = ITK_NULLPTR;
itkDebugMacro("Interpolator is BSpline");
}
//
// Check if the transform is of type BSplineTransform.
//
// If so, several speed up features are implemented.
// [1] Precomputing the results of bulk transform for each sample point.
// [2] Precomputing the BSpline weights for each sample point,
// to be used later to directly compute the deformation vector
// [3] Precomputing the indices of the parameters within the
// the support region of each sample point.
//
m_TransformIsBSpline = true;
BSplineTransformType *testPtr2 = dynamic_cast< BSplineTransformType * >(
this->m_Transform.GetPointer() );
if ( !testPtr2 )
{
m_TransformIsBSpline = false;
m_BSplineTransform = ITK_NULLPTR;
itkDebugMacro("Transform is not BSplineDeformable");
}
else
{
m_BSplineTransform = testPtr2;
m_NumBSplineWeights = m_BSplineTransform->GetNumberOfWeights();
itkDebugMacro("Transform is BSplineDeformable");
}
if ( this->m_TransformIsBSpline )
{
// First, deallocate memory that may have been used from previous run of the Metric
this->m_BSplineTransformWeightsArray.SetSize(1, 1);
this->m_BSplineTransformIndicesArray.SetSize(1, 1);
this->m_BSplinePreTransformPointsArray.resize(1);
this->m_WithinBSplineSupportRegionArray.resize(1);
this->m_BSplineTransformWeights.SetSize(1);
this->m_BSplineTransformIndices.SetSize(1);
delete[] this->m_ThreaderBSplineTransformWeights;
this->m_ThreaderBSplineTransformWeights = ITK_NULLPTR;
delete[] this->m_ThreaderBSplineTransformIndices;
this->m_ThreaderBSplineTransformIndices = ITK_NULLPTR;
if ( this->m_UseCachingOfBSplineWeights )
{
m_BSplineTransformWeightsArray.SetSize(
m_NumberOfFixedImageSamples, m_NumBSplineWeights);
m_BSplineTransformIndicesArray.SetSize(
m_NumberOfFixedImageSamples, m_NumBSplineWeights);
m_BSplinePreTransformPointsArray.resize(m_NumberOfFixedImageSamples);
m_WithinBSplineSupportRegionArray.resize(m_NumberOfFixedImageSamples);
this->PreComputeTransformValues();
}
else
{
this->m_BSplineTransformWeights.SetSize(this->m_NumBSplineWeights);
this->m_BSplineTransformIndices.SetSize(this->m_NumBSplineWeights);
this->m_ThreaderBSplineTransformWeights = new BSplineTransformWeightsType[m_NumberOfThreads - 1];
this->m_ThreaderBSplineTransformIndices = new BSplineTransformIndexArrayType[m_NumberOfThreads - 1];
for ( ThreadIdType ithread = 0; ithread < m_NumberOfThreads - 1; ++ithread )
{
this->m_ThreaderBSplineTransformWeights[ithread].SetSize(this->m_NumBSplineWeights);
this->m_ThreaderBSplineTransformIndices[ithread].SetSize(this->m_NumBSplineWeights);
}
}
for ( unsigned int j = 0; j < FixedImageDimension; j++ )
{
this->m_BSplineParametersOffset[j] = j * this->m_BSplineTransform->GetNumberOfParametersPerDimension();
}
}
}
/**
* Use the indexes that have been passed to the metric
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SampleFixedImageIndexes(FixedImageSampleContainer & samples) const
{
typename FixedImageSampleContainer::iterator iter;
SizeValueType len = static_cast<SizeValueType>( m_FixedImageIndexes.size() );
if ( len != m_NumberOfFixedImageSamples
|| samples.size() != m_NumberOfFixedImageSamples )
{
throw ExceptionObject(__FILE__, __LINE__,
"Index list size does not match desired number of samples");
}
iter = samples.begin();
for ( SizeValueType i = 0; i < len; i++ )
{
// Get sampled index
FixedImageIndexType index = m_FixedImageIndexes[i];
// Translate index to point
m_FixedImage->TransformIndexToPhysicalPoint(index, ( *iter ).point);
// Get sampled fixed image value
( *iter ).value = m_FixedImage->GetPixel(index);
( *iter ).valueIndex = 0;
++iter;
}
}
/**
* Sample the fixed image using a random walk
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SampleFixedImageRegion(FixedImageSampleContainer & samples) const
{
if ( samples.size() != m_NumberOfFixedImageSamples )
{
throw ExceptionObject(__FILE__, __LINE__,
"Sample size does not match desired number of samples");
}
// Set up a random interator within the user specified fixed image region.
typedef ImageRandomConstIteratorWithIndex< FixedImageType > RandomIterator;
RandomIterator randIter( m_FixedImage, GetFixedImageRegion() );
typename FixedImageSampleContainer::iterator iter;
typename FixedImageSampleContainer::const_iterator end = samples.end();
if ( m_FixedImageMask.IsNotNull()
|| m_UseFixedImageSamplesIntensityThreshold )
{
InputPointType inputPoint;
iter = samples.begin();
SizeValueType samplesFound = 0;
randIter.SetNumberOfSamples(m_NumberOfFixedImageSamples * 1000);
randIter.GoToBegin();
while ( iter != end )
{
if ( randIter.IsAtEnd() )
{
// Must be a small mask since after many random samples we don't
// have enough to fill the desired number. So, we will replicate
// the samples we've found so far to fill-in the desired number
// of samples
SizeValueType count = 0;
while ( iter != end )
{
( *iter ).point = samples[count].point;
( *iter ).value = samples[count].value;
( *iter ).valueIndex = 0;
++count;
if ( count >= samplesFound )
{
count = 0;
}
++iter;
}
break;
}
// Get sampled index
FixedImageIndexType index = randIter.GetIndex();
// Check if the Index is inside the mask, translate index to point
m_FixedImage->TransformIndexToPhysicalPoint(index, inputPoint);
if ( m_FixedImageMask.IsNotNull() )
{
double val;
if ( m_FixedImageMask->ValueAt(inputPoint, val) )
{
if ( Math::AlmostEquals( val, 0.0 ) )
{
++randIter; // jump to another random position
continue;
}
}
else
{
++randIter; // jump to another random position
continue;
}
}
if ( m_UseFixedImageSamplesIntensityThreshold
&& randIter.Get() < m_FixedImageSamplesIntensityThreshold )
{
++randIter;
continue;
}
// Translate index to point
( *iter ).point = inputPoint;
// Get sampled fixed image value
( *iter ).value = randIter.Get();
( *iter ).valueIndex = 0;
++samplesFound;
++randIter;
++iter;
}
}
else
{
randIter.SetNumberOfSamples(m_NumberOfFixedImageSamples);
randIter.GoToBegin();
for ( iter = samples.begin(); iter != end; ++iter )
{
// Get sampled index
FixedImageIndexType index = randIter.GetIndex();
// Translate index to point
m_FixedImage->TransformIndexToPhysicalPoint(index,
( *iter ).point);
// Get sampled fixed image value
( *iter ).value = randIter.Get();
( *iter ).valueIndex = 0;
// Jump to random position
++randIter;
}
}
}
/**
* Sample the fixed image domain using all pixels in the Fixed image region
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::SampleFullFixedImageRegion(FixedImageSampleContainer & samples) const
{
if ( samples.size() != m_NumberOfFixedImageSamples )
{
throw ExceptionObject(__FILE__, __LINE__,
"Sample size does not match desired number of samples");
}
// Set up a region interator within the user specified fixed image region.
typedef ImageRegionConstIteratorWithIndex< FixedImageType > RegionIterator;
RegionIterator regionIter( m_FixedImage, GetFixedImageRegion() );
regionIter.GoToBegin();
typename FixedImageSampleContainer::iterator iter;
typename FixedImageSampleContainer::const_iterator end = samples.end();
if ( m_FixedImageMask.IsNotNull()
|| m_UseFixedImageSamplesIntensityThreshold )
{
InputPointType inputPoint;
// repeat until we get enough samples to fill the array
iter = samples.begin();
while ( iter != end )
{
// Get sampled index
FixedImageIndexType index = regionIter.GetIndex();
// Check if the Index is inside the mask, translate index to point
m_FixedImage->TransformIndexToPhysicalPoint(index, inputPoint);
if ( m_FixedImageMask.IsNotNull() )
{
// If not inside the mask, ignore the point
if ( !m_FixedImageMask->IsInside(inputPoint) )
{
++regionIter; // jump to next pixel
if ( regionIter.IsAtEnd() )
{
regionIter.GoToBegin();
}
continue;
}
}
if ( m_UseFixedImageSamplesIntensityThreshold
&& regionIter.Get() < m_FixedImageSamplesIntensityThreshold )
{
++regionIter; // jump to next pixel
if ( regionIter.IsAtEnd() )
{
regionIter.GoToBegin();
}
continue;
}
// Translate index to point
( *iter ).point = inputPoint;
// Get sampled fixed image value
( *iter ).value = regionIter.Get();
( *iter ).valueIndex = 0;
++regionIter;
if ( regionIter.IsAtEnd() )
{
regionIter.GoToBegin();
}
++iter;
}
}
else // not restricting sample throwing to a mask
{
for ( iter = samples.begin(); iter != end; ++iter )
{
// Get sampled index
FixedImageIndexType index = regionIter.GetIndex();
// Translate index to point
m_FixedImage->TransformIndexToPhysicalPoint(index,
( *iter ).point);
// Get sampled fixed image value
( *iter ).value = regionIter.Get();
( *iter ).valueIndex = 0;
++regionIter;
if ( regionIter.IsAtEnd() )
{
regionIter.GoToBegin();
}
}
}
}
/**
* Compute the gradient image and assign it to m_GradientImage.
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::ComputeGradient()
{
GradientImageFilterPointer gradientFilter = GradientImageFilterType::New();
gradientFilter->SetInput(m_MovingImage);
const typename MovingImageType::SpacingType & spacing = m_MovingImage
->GetSpacing();
double maximumSpacing = 0.0;
for ( unsigned int i = 0; i < MovingImageDimension; i++ )
{
if ( spacing[i] > maximumSpacing )
{
maximumSpacing = spacing[i];
}
}
gradientFilter->SetSigma(maximumSpacing);
gradientFilter->SetNormalizeAcrossScale(true);
gradientFilter->SetNumberOfThreads(m_NumberOfThreads);
gradientFilter->SetUseImageDirection(true);
gradientFilter->Update();
m_GradientImage = gradientFilter->GetOutput();
}
// Method to reinitialize the seed of the random number generator
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::ReinitializeSeed()
{
Statistics::MersenneTwisterRandomVariateGenerator::GetInstance()->SetSeed();
}
// Method to reinitialize the seed of the random number generator
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::ReinitializeSeed(int seed)
{
Statistics::MersenneTwisterRandomVariateGenerator::GetInstance()->SetSeed(
seed);
}
/**
* Cache pre-transformed points, weights and indices.
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::PreComputeTransformValues()
{
// Note: This code is specific to the b-spline deformable transform.
// Unfortunately, the BSplineTransform stores a
// pointer to parameters passed to SetParameters(). Since
// we're creating a dummy set of parameters below on the
// stack, this can cause a crash if the transform's
// parameters are not later reset with a more properly
// scoped set of parameters. In addition, we're overwriting
// any previously set parameters. In order to be kinder,
// we'll save a pointer to the current set of parameters
// and restore them after we're done.
// Note the address operator.
// const TransformParametersType* previousParameters = &
// m_Transform->GetParameters();
// Create all zero dummy transform parameters
ParametersType dummyParameters(m_NumberOfParameters);
dummyParameters.Fill(0.0);
m_Transform->SetParameters(dummyParameters);
// Cycle through each sampled fixed image point
BSplineTransformWeightsType weights(m_NumBSplineWeights);
BSplineTransformIndexArrayType indices(m_NumBSplineWeights);
bool valid;
MovingImagePointType mappedPoint;
// Declare iterators for iteration over the sample container
typename FixedImageSampleContainer::const_iterator fiter;
typename FixedImageSampleContainer::const_iterator fend =
m_FixedImageSamples.end();
SizeValueType counter = 0;
for ( fiter = m_FixedImageSamples.begin(); fiter != fend; ++fiter, counter++ )
{
m_BSplineTransform->TransformPoint(m_FixedImageSamples[counter].point,
mappedPoint, weights, indices, valid);
for ( SizeValueType k = 0; k < m_NumBSplineWeights; k++ )
{
m_BSplineTransformWeightsArray[counter][k] = weights[k];
m_BSplineTransformIndicesArray[counter][k] = indices[k];
}
m_BSplinePreTransformPointsArray[counter] = mappedPoint;
m_WithinBSplineSupportRegionArray[counter] = valid;
}
// Restore the previous parameters.
// m_Transform->SetParameters( *previousParameters );
}
/**
* Transform a point from FixedImage domain to MovingImage domain.
* This function also checks if mapped point is within support region.
*/
template< typename TFixedImage, typename TMovingImage >
void
ImageToImageMetric< TFixedImage, TMovingImage >
::TransformPoint(unsigned int sampleNumber,
MovingImagePointType & mappedPoint,
bool & sampleOk,
double & movingImageValue,
ThreadIdType threadId) const
{
sampleOk = true;
TransformType *transform;
if ( threadId > 0 )
{
transform = this->m_ThreaderTransform[threadId - 1];
}
else
{
transform = this->m_Transform;
}
if ( !m_TransformIsBSpline )
{
// Use generic transform to compute mapped position
mappedPoint = transform->TransformPoint(m_FixedImageSamples[sampleNumber].point);
sampleOk = true;
}
else
{
if ( this->m_UseCachingOfBSplineWeights )
{
sampleOk = m_WithinBSplineSupportRegionArray[sampleNumber];
if ( sampleOk )
{
// If the transform is BSplineDeformable, we can use the precomputed
// weights and indices to obtained the mapped position
const WeightsValueType *weights =
m_BSplineTransformWeightsArray[sampleNumber];
const IndexValueType *indices =
m_BSplineTransformIndicesArray[sampleNumber];
for ( unsigned int j = 0; j < FixedImageDimension; j++ )
{
mappedPoint[j] = m_BSplinePreTransformPointsArray[sampleNumber][j];
}
const ParametersType &LocalParameters = m_Transform->GetParameters();
for ( unsigned int k = 0; k < m_NumBSplineWeights; k++ )
{
for ( unsigned int j = 0; j < FixedImageDimension; j++ )
{
mappedPoint[j] += weights[k] * LocalParameters[indices[k]
+ m_BSplineParametersOffset[j]];
}
}
}
}
else
{
BSplineTransformWeightsType * weightsHelper;
BSplineTransformIndexArrayType *indicesHelper;
if ( threadId > 0 )
{
weightsHelper = &( this->m_ThreaderBSplineTransformWeights[threadId - 1] );
indicesHelper = &( this->m_ThreaderBSplineTransformIndices[threadId - 1] );
}
else
{
weightsHelper = &( this->m_BSplineTransformWeights );
indicesHelper = &( this->m_BSplineTransformIndices );
}
// If not caching values, we invoke the Transform to recompute the
// mapping of the point.
this->m_BSplineTransform->TransformPoint(
this->m_FixedImageSamples[sampleNumber].point,
mappedPoint, *weightsHelper, *indicesHelper, sampleOk);
}
}
if ( sampleOk )
{
// If user provided a mask over the Moving image
if ( m_MovingImageMask )
{
// Check if mapped point is within the support region of the moving image
// mask
sampleOk = sampleOk && m_MovingImageMask->IsInside(mappedPoint);
}
if ( m_InterpolatorIsBSpline )
{
// Check if mapped point inside image buffer
sampleOk = sampleOk && m_BSplineInterpolator->IsInsideBuffer(mappedPoint);
if ( sampleOk )
{
movingImageValue = m_BSplineInterpolator->Evaluate(mappedPoint, threadId);
}
}
else
{
// Check if mapped point inside image buffer
sampleOk = sampleOk && m_Interpolator->IsInsideBuffer(mappedPoint);
if ( sampleOk )
{
movingImageValue = m_Interpolator->Evaluate(mappedPoint);
}
}
}