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itkObjectToObjectMultiMetricv4Test.cxx
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itkObjectToObjectMultiMetricv4Test.cxx
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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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.
*
*=========================================================================*/
#include "itkObjectToObjectMultiMetricv4.h"
#include "itkMeanSquaresImageToImageMetricv4.h"
#include "itkMattesMutualInformationImageToImageMetricv4.h"
#include "itkJointHistogramMutualInformationImageToImageMetricv4.h"
#include "itkANTSNeighborhoodCorrelationImageToImageMetricv4.h"
#include "itkTranslationTransform.h"
#include "itkLinearInterpolateImageFunction.h"
#include "itkImage.h"
#include "itkGaussianImageSource.h"
#include "itkShiftScaleImageFilter.h"
#include "itkTestingMacros.h"
#include "itkCompositeTransform.h"
#include "itkEuclideanDistancePointSetToPointSetMetricv4.h"
#include "itkExpectationBasedPointSetToPointSetMetricv4.h"
#include "itkRegistrationParameterScalesFromPhysicalShift.h"
/** This test illustrates the use of the MultivariateImageToImageMetric class, which
takes N metrics and assigns a weight to each metric's result.
*/
constexpr unsigned int ObjectToObjectMultiMetricv4TestDimension = 2;
using ObjectToObjectMultiMetricv4TestMultiMetricType =
itk::ObjectToObjectMultiMetricv4<ObjectToObjectMultiMetricv4TestDimension, ObjectToObjectMultiMetricv4TestDimension>;
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
int
itkObjectToObjectMultiMetricv4TestEvaluate(ObjectToObjectMultiMetricv4TestMultiMetricType::Pointer & multiVariateMetric,
bool useDisplacementTransform)
{
int testStatus = EXIT_SUCCESS;
using MultiMetricType = ObjectToObjectMultiMetricv4TestMultiMetricType;
// Setup weights
MultiMetricType::WeightsArrayType origMetricWeights(multiVariateMetric->GetNumberOfMetrics());
MultiMetricType::WeightValueType weightSum = 0;
for (itk::SizeValueType n = 0; n < multiVariateMetric->GetNumberOfMetrics(); ++n)
{
origMetricWeights[n] = static_cast<MultiMetricType::WeightValueType>(n + 1);
weightSum += origMetricWeights[n];
}
multiVariateMetric->SetMetricWeights(origMetricWeights);
// Initialize. This initializes all the component metrics.
std::cout << "Initialize" << std::endl;
multiVariateMetric->Initialize();
// Print out metric value and derivative.
using MeasureType = MultiMetricType::MeasureType;
MeasureType measure = 0;
MultiMetricType::DerivativeType DerivResultOfGetValueAndDerivative;
std::cout << "GetValueAndDerivative" << std::endl;
try
{
multiVariateMetric->GetValueAndDerivative(measure, DerivResultOfGetValueAndDerivative);
}
catch (const itk::ExceptionObject & exp)
{
std::cerr << "Exception caught during call to GetValueAndDerivative:" << std::endl;
std::cerr << exp << std::endl;
testStatus = EXIT_FAILURE;
}
std::cout << "Multivariate measure: " << measure << std::endl;
if (!useDisplacementTransform)
{
std::cout << " Derivative : " << DerivResultOfGetValueAndDerivative << std::endl << std::endl;
}
// Test GetDerivative
MultiMetricType::DerivativeType ResultOfGetDerivative;
multiVariateMetric->GetDerivative(ResultOfGetDerivative);
for (MultiMetricType::NumberOfParametersType p = 0; p < multiVariateMetric->GetNumberOfParameters(); ++p)
{
// When accumulation is done accross multiple threads, the accumulations can be done
// in different orders resulting in slightly different numerical results.
// The FloatAlmostEqual is used to address the multi-threaded accumulation differences
if (!itk::Math::FloatAlmostEqual(ResultOfGetDerivative[p], DerivResultOfGetValueAndDerivative[p], 8, 1e-15))
{
std::cerr << "Results do not match between GetValueAndDerivative and GetDerivative." << std::endl;
std::cout << ResultOfGetDerivative << " != " << DerivResultOfGetValueAndDerivative << std::endl;
std::cout << "DIFF: " << ResultOfGetDerivative - DerivResultOfGetValueAndDerivative << std::endl;
testStatus = EXIT_FAILURE;
}
}
// Test GetValue method
MeasureType measure2 = 0;
std::cout << "GetValue" << std::endl;
try
{
measure2 = multiVariateMetric->GetValue();
}
catch (const itk::ExceptionObject & exp)
{
std::cerr << "Exception caught during call to GetValue:" << std::endl;
std::cerr << exp << std::endl;
testStatus = EXIT_FAILURE;
}
if (!itk::Math::FloatAlmostEqual(measure2, measure))
{
std::cerr << "measure does not match between calls to GetValue and GetValueAndDerivative: "
<< "measure: " << measure << " measure2: " << measure2 << std::endl;
testStatus = EXIT_FAILURE;
}
// Evaluate individually
MeasureType metricValue = itk::NumericTraits<MeasureType>::ZeroValue();
MeasureType weightedMetricValue = itk::NumericTraits<MeasureType>::ZeroValue();
MultiMetricType::DerivativeType metricDerivative;
MultiMetricType::DerivativeType DerivResultOfGetValueAndDerivativeTruth(multiVariateMetric->GetNumberOfParameters());
DerivResultOfGetValueAndDerivativeTruth.Fill(itk::NumericTraits<MultiMetricType::DerivativeValueType>::ZeroValue());
MultiMetricType::DerivativeValueType totalMagnitude =
itk::NumericTraits<MultiMetricType::DerivativeValueType>::ZeroValue();
for (itk::SizeValueType i = 0; i < multiVariateMetric->GetNumberOfMetrics(); ++i)
{
std::cout << "GetValueAndDerivative on component metrics" << std::endl;
multiVariateMetric->GetMetricQueue()[i]->GetValueAndDerivative(metricValue, metricDerivative);
std::cout << " Metric " << i << " value : " << metricValue << std::endl;
if (!useDisplacementTransform)
{
std::cout << " Metric " << i << " derivative : " << metricDerivative << std::endl << std::endl;
}
if (!itk::Math::FloatAlmostEqual(metricValue, multiVariateMetric->GetValueArray()[i]))
{
std::cerr << "Individual metric value " << metricValue
<< " does not match that returned from multi-variate metric: " << multiVariateMetric->GetValueArray()[i]
<< std::endl;
testStatus = EXIT_FAILURE;
}
weightedMetricValue += metricValue * origMetricWeights[i] / weightSum;
for (MultiMetricType::NumberOfParametersType p = 0; p < multiVariateMetric->GetNumberOfParameters(); ++p)
{
DerivResultOfGetValueAndDerivativeTruth[p] +=
metricDerivative[p] * (origMetricWeights[i] / weightSum) / metricDerivative.magnitude();
}
totalMagnitude += metricDerivative.magnitude();
}
totalMagnitude /= multiVariateMetric->GetNumberOfMetrics();
for (MultiMetricType::NumberOfParametersType p = 0; p < multiVariateMetric->GetNumberOfParameters(); ++p)
{
DerivResultOfGetValueAndDerivativeTruth[p] *= totalMagnitude;
}
if (itk::Math::abs(weightedMetricValue - multiVariateMetric->GetWeightedValue()) > 1e-6)
{
std::cerr << "Computed weighted metric value " << weightedMetricValue << " does match returned value "
<< multiVariateMetric->GetWeightedValue() << std::endl;
testStatus = EXIT_FAILURE;
}
for (MultiMetricType::NumberOfParametersType p = 0; p < multiVariateMetric->GetNumberOfParameters(); ++p)
{
auto tolerance = static_cast<MultiMetricType::DerivativeValueType>(1e-6);
if (itk::Math::abs(DerivResultOfGetValueAndDerivativeTruth[p] - DerivResultOfGetValueAndDerivative[p]) > tolerance)
{
std::cerr << "Error: DerivResultOfGetValueAndDerivative does not match expected result." << std::endl;
if (useDisplacementTransform)
{
std::cerr << " DerivResultOfGetValueAndDerivative[" << p << "]: " << DerivResultOfGetValueAndDerivative[p]
<< std::endl
<< " DerivResultOfGetValueAndDerivativeTruth[" << p
<< "]: " << DerivResultOfGetValueAndDerivativeTruth[p] << std::endl;
}
else
{
std::cerr << " DerivResultOfGetValueAndDerivative: " << DerivResultOfGetValueAndDerivative << std::endl
<< " DerivResultOfGetValueAndDerivativeTruth: " << DerivResultOfGetValueAndDerivativeTruth
<< std::endl;
}
testStatus = EXIT_FAILURE;
}
}
return testStatus;
}
////////////////////////////////////////////////////////////
int
itkObjectToObjectMultiMetricv4TestRun(bool useDisplacementTransform)
{
// Create two simple images
const unsigned int Dimension = ObjectToObjectMultiMetricv4TestDimension;
using PixelType = double;
using CoordinateRepresentationType = double;
// Allocate Images
using FixedImageType = itk::Image<PixelType, Dimension>;
using MovingImageType = itk::Image<PixelType, Dimension>;
// Declare Gaussian Sources
using FixedImageSourceType = itk::GaussianImageSource<FixedImageType>;
// Note: the following declarations are classical arrays
FixedImageType::SizeValueType fixedImageSize[] = { 100, 100 };
FixedImageType::SpacingValueType fixedImageSpacing[] = { 1.0f, 1.0f };
FixedImageType::PointValueType fixedImageOrigin[] = { 0.0f, 0.0f };
auto fixedImageSource = FixedImageSourceType::New();
fixedImageSource->SetSize(fixedImageSize);
fixedImageSource->SetOrigin(fixedImageOrigin);
fixedImageSource->SetSpacing(fixedImageSpacing);
fixedImageSource->SetNormalized(false);
fixedImageSource->SetScale(1.0f);
fixedImageSource->Update(); // Force the filter to run
FixedImageType::Pointer fixedImage = fixedImageSource->GetOutput();
using ShiftScaleFilterType = itk::ShiftScaleImageFilter<FixedImageType, MovingImageType>;
auto shiftFilter = ShiftScaleFilterType::New();
shiftFilter->SetInput(fixedImage);
shiftFilter->SetShift(2.0);
shiftFilter->Update();
MovingImageType::Pointer movingImage = shiftFilter->GetOutput();
// Set up the metric.
using MultiMetricType = ObjectToObjectMultiMetricv4TestMultiMetricType;
auto multiVariateMetric = MultiMetricType::New();
// Instantiate and Add metrics to the queue
using JointHistorgramMetrictype =
itk::JointHistogramMutualInformationImageToImageMetricv4<FixedImageType, MovingImageType>;
using MeanSquaresMetricType = itk::MeanSquaresImageToImageMetricv4<FixedImageType, MovingImageType>;
using MattesMutualInformationMetricType =
itk::MattesMutualInformationImageToImageMetricv4<FixedImageType, MovingImageType>;
using ANTSNCMetricType = itk::ANTSNeighborhoodCorrelationImageToImageMetricv4<FixedImageType, MovingImageType>;
auto m1 = MeanSquaresMetricType::New();
auto m2 = MattesMutualInformationMetricType::New();
auto m3 = JointHistorgramMetrictype::New();
auto m4 = ANTSNCMetricType::New();
// Set up a transform
using TransformType = itk::Transform<CoordinateRepresentationType, Dimension, Dimension>;
using DisplacementTransformType = itk::DisplacementFieldTransform<double, Dimension>;
using TranslationTransformType = itk::TranslationTransform<CoordinateRepresentationType, Dimension>;
TransformType::Pointer transform;
if (useDisplacementTransform)
{
using FieldType = DisplacementTransformType::DisplacementFieldType;
using VectorType = itk::Vector<double, Dimension>;
VectorType zero;
zero.Fill(0.0);
auto field = FieldType::New();
field->SetRegions(fixedImage->GetBufferedRegion());
field->SetSpacing(fixedImage->GetSpacing());
field->SetOrigin(fixedImage->GetOrigin());
field->Allocate();
field->FillBuffer(zero);
auto displacementTransform = DisplacementTransformType::New();
displacementTransform->SetDisplacementField(field);
transform = displacementTransform;
}
else
{
auto translationTransform = TranslationTransformType::New();
translationTransform->SetIdentity();
transform = translationTransform;
}
// Plug the images and transform into the metrics
std::cout << "Setup metrics" << std::endl;
m1->SetFixedImage(fixedImage);
m1->SetMovingImage(movingImage);
m1->SetMovingTransform(transform);
m2->SetFixedImage(fixedImage);
m2->SetMovingImage(movingImage);
m2->SetMovingTransform(transform);
m3->SetFixedImage(fixedImage);
m3->SetMovingImage(movingImage);
m3->SetMovingTransform(transform);
m4->SetFixedImage(fixedImage);
m4->SetMovingImage(movingImage);
m4->SetMovingTransform(transform);
// Add the component metrics
std::cout << "Add component metrics" << std::endl;
multiVariateMetric->AddMetric(m1);
multiVariateMetric->AddMetric(m2);
multiVariateMetric->AddMetric(m3);
multiVariateMetric->AddMetric(m4);
if (multiVariateMetric->GetMetricQueue()[0] != m1 || multiVariateMetric->GetMetricQueue()[3] != m4)
{
std::cerr << "AddMetric or GetMetricQueue failed." << std::endl;
return EXIT_FAILURE;
}
// Expect return true because all image metrics
if (multiVariateMetric->SupportsArbitraryVirtualDomainSamples() == false)
{
std::cerr << "Expected SupportsArbitraryVirtualDomainSamples() to return false, but got true. " << std::endl;
return EXIT_FAILURE;
}
// Test Set/Get Transform mechanics
multiVariateMetric->Initialize();
if (multiVariateMetric->GetMovingTransform() != transform.GetPointer())
{
std::cerr << "Automatic transform assignment failed. transform: " << transform.GetPointer()
<< " GetMovingTranform: " << multiVariateMetric->GetMovingTransform() << std::endl;
return EXIT_FAILURE;
}
multiVariateMetric->SetMovingTransform(nullptr);
for (itk::SizeValueType n = 0; n < multiVariateMetric->GetNumberOfMetrics(); ++n)
{
if (multiVariateMetric->GetMovingTransform() != nullptr ||
multiVariateMetric->GetMetricQueue()[n]->GetMovingTransform() != nullptr)
{
std::cerr << "Assignment of null transform failed. multiVariateMetric->GetMovingTransform(): "
<< multiVariateMetric->GetMovingTransform() << " multiVariateMetric->GetMetricQueue()[" << n
<< "]->GetMovingTransform(): " << multiVariateMetric->GetMetricQueue()[n]->GetMovingTransform()
<< std::endl;
return EXIT_FAILURE;
}
}
multiVariateMetric->SetMovingTransform(transform);
for (itk::SizeValueType n = 0; n < multiVariateMetric->GetNumberOfMetrics(); ++n)
{
if (multiVariateMetric->GetMovingTransform() != transform.GetPointer() ||
multiVariateMetric->GetMetricQueue()[0]->GetMovingTransform() != transform.GetPointer())
{
std::cerr << "Assignment of transform failed." << std::endl;
return EXIT_FAILURE;
}
}
if (multiVariateMetric->GetMovingTransform() != transform.GetPointer())
{
std::cerr << "Retrieval of transform failed." << std::endl;
}
// Test with images
std::cout << "*** Test image metrics *** " << std::endl;
if (itkObjectToObjectMultiMetricv4TestEvaluate(multiVariateMetric, useDisplacementTransform) != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
std::cout << "*** Test with mismatched transforms *** " << std::endl;
auto transform2 = TranslationTransformType::New();
m4->SetMovingTransform(transform2);
ITK_TRY_EXPECT_EXCEPTION(multiVariateMetric->Initialize());
m4->SetMovingTransform(transform);
std::cout << "*** Test with proper CompositeTransform ***" << std::endl;
using CompositeTransformType = itk::CompositeTransform<CoordinateRepresentationType, Dimension>;
auto compositeTransform = CompositeTransformType::New();
compositeTransform->AddTransform(transform2);
compositeTransform->AddTransform(transform);
compositeTransform->SetOnlyMostRecentTransformToOptimizeOn();
m4->SetMovingTransform(compositeTransform);
if (itkObjectToObjectMultiMetricv4TestEvaluate(multiVariateMetric, useDisplacementTransform) != EXIT_SUCCESS)
{
std::cerr << "Failed with proper CompositeTransform." << std::endl;
return EXIT_FAILURE;
}
std::cout << "*** Test with CompositeTransform - too many active transforms ***" << std::endl;
compositeTransform->SetAllTransformsToOptimizeOn();
ITK_TRY_EXPECT_EXCEPTION(multiVariateMetric->Initialize());
std::cout << "*** Test with CompositeTransform - one active transform, but wrong one ***" << std::endl;
compositeTransform->SetAllTransformsToOptimizeOff();
compositeTransform->SetNthTransformToOptimizeOn(0);
ITK_TRY_EXPECT_EXCEPTION(multiVariateMetric->Initialize());
// Reset transform
m4->SetMovingTransform(transform);
//
// Test with adding point set metrics
//
using PointSetType = itk::PointSet<float, Dimension>;
auto fixedPoints = PointSetType::New();
auto movingPoints = PointSetType::New();
fixedPoints->Initialize();
movingPoints->Initialize();
PointSetType::PointType point;
for (itk::SizeValueType n = 0; n < 100; ++n)
{
point[0] = n * 1.0;
point[1] = n * 2.0;
fixedPoints->SetPoint(n, point);
point[0] += 0.5;
point[1] += 0.5;
movingPoints->SetPoint(n, point);
}
using ExpectationPointSetMetricType = itk::ExpectationBasedPointSetToPointSetMetricv4<PointSetType>;
using EuclideanPointSetMetricType = itk::EuclideanDistancePointSetToPointSetMetricv4<PointSetType>;
auto expectationPointSetMetric = ExpectationPointSetMetricType::New();
auto euclideanPointSetMetric = EuclideanPointSetMetricType::New();
expectationPointSetMetric->SetFixedPointSet(fixedPoints);
expectationPointSetMetric->SetMovingPointSet(movingPoints);
expectationPointSetMetric->SetMovingTransform(transform);
euclideanPointSetMetric->SetFixedPointSet(fixedPoints);
euclideanPointSetMetric->SetMovingPointSet(movingPoints);
euclideanPointSetMetric->SetMovingTransform(transform);
multiVariateMetric->AddMetric(expectationPointSetMetric);
multiVariateMetric->AddMetric(euclideanPointSetMetric);
// Expect return false because of point set metrics
if (multiVariateMetric->SupportsArbitraryVirtualDomainSamples() == true)
{
std::cerr << "Expected SupportsArbitraryVirtualDomainSamples() to return true, but got false. " << std::endl;
return EXIT_FAILURE;
}
// Test
std::cout << "*** Test with PointSet metrics and Image metrics *** " << std::endl;
if (itkObjectToObjectMultiMetricv4TestEvaluate(multiVariateMetric, useDisplacementTransform) != EXIT_SUCCESS)
{
return EXIT_FAILURE;
}
//
// Exercise basic operation with a scales estimator
//
using ScalesEstimatorMultiType = itk::RegistrationParameterScalesFromPhysicalShift<MultiMetricType>;
auto shiftScaleEstimator = ScalesEstimatorMultiType::New();
shiftScaleEstimator->SetMetric(multiVariateMetric);
// Have to assign virtual domain sampling points when using a point set with scales estimator
shiftScaleEstimator->SetVirtualDomainPointSet(expectationPointSetMetric->GetVirtualTransformedPointSet());
ScalesEstimatorMultiType::ScalesType scales;
shiftScaleEstimator->EstimateScales(scales);
std::cout << "Estimated scales: " << scales << std::endl;
ScalesEstimatorMultiType::FloatType stepScale;
ScalesEstimatorMultiType::ParametersType step;
step.SetSize(multiVariateMetric->GetNumberOfParameters());
step.Fill(itk::NumericTraits<ScalesEstimatorMultiType::ParametersType::ValueType>::OneValue());
stepScale = shiftScaleEstimator->EstimateStepScale(step);
std::cout << "Estimated stepScale: " << stepScale << std::endl;
//
// Test that we get the same scales/step estimation
// with a single metric and the same metric twice in a multimetric
//
ScalesEstimatorMultiType::ScalesType singleScales, multiSingleScales, multiDoubleScales;
ScalesEstimatorMultiType::FloatType singleStep, multiSingleStep, multiDoubleStep;
step.SetSize(m1->GetNumberOfParameters());
step.Fill(itk::NumericTraits<ScalesEstimatorMultiType::ParametersType::ValueType>::OneValue());
using ScalesEstimatorMeanSquaresType = itk::RegistrationParameterScalesFromPhysicalShift<MeanSquaresMetricType>;
auto singleShiftScaleEstimator = ScalesEstimatorMeanSquaresType::New();
singleShiftScaleEstimator->SetMetric(m1);
m1->Initialize();
singleShiftScaleEstimator->EstimateScales(singleScales);
std::cout << "Single metric estimated scales: " << singleScales << std::endl;
singleStep = singleShiftScaleEstimator->EstimateStepScale(step);
std::cout << "Single metric estimated stepScale: " << singleStep << std::endl;
auto multiSingleMetric = MultiMetricType::New();
multiSingleMetric->AddMetric(m1);
multiSingleMetric->Initialize();
shiftScaleEstimator->SetMetric(multiSingleMetric);
shiftScaleEstimator->EstimateScales(multiSingleScales);
std::cout << "multi-single estimated scales: " << multiSingleScales << std::endl;
multiSingleStep = shiftScaleEstimator->EstimateStepScale(step);
std::cout << "multi-single estimated stepScale: " << multiSingleStep << std::endl;
auto multiDoubleMetric = MultiMetricType::New();
multiDoubleMetric->AddMetric(m1);
multiDoubleMetric->AddMetric(m1);
multiDoubleMetric->Initialize();
shiftScaleEstimator->SetMetric(multiDoubleMetric);
shiftScaleEstimator->EstimateScales(multiDoubleScales);
std::cout << "multi-double estimated scales: " << multiDoubleScales << std::endl;
multiDoubleStep = shiftScaleEstimator->EstimateStepScale(step);
std::cout << "multi-double estimated stepScale: " << multiDoubleStep << std::endl;
// Check that results are the same for all three estimations
bool passedEstimation = true;
auto tolerance = static_cast<ScalesEstimatorMultiType::FloatType>(1e-6);
if (itk::Math::abs(singleStep - multiSingleStep) > tolerance ||
itk::Math::abs(singleStep - multiDoubleStep) > tolerance)
{
std::cerr << "Steps do not match as expected between estimation on same metric." << std::endl;
passedEstimation = false;
}
if (itk::Math::abs(singleScales[0] - multiSingleScales[0]) > tolerance ||
itk::Math::abs(singleScales[1] - multiSingleScales[1]) > tolerance ||
itk::Math::abs(singleScales[0] - multiDoubleScales[0]) > tolerance ||
itk::Math::abs(singleScales[1] - multiDoubleScales[1]) > tolerance)
{
std::cerr << "Scales do not match as expected between estimation on same metric." << std::endl;
passedEstimation = false;
}
if (!passedEstimation)
{
return EXIT_FAILURE;
}
if (!useDisplacementTransform)
{
// Exercising the Print function
std::cout << "Print: " << std::endl;
multiVariateMetric->Print(std::cout);
// Test ClearMetricQueue
multiVariateMetric->ClearMetricQueue();
if (multiVariateMetric->GetNumberOfMetrics() != 0)
{
std::cerr << "ClearMetricQueue() failed. Number of metrics is not zero." << std::endl;
return EXIT_FAILURE;
}
}
return EXIT_SUCCESS;
}
int
itkObjectToObjectMultiMetricv4Test(int, char *[])
{
std::cout << "XXX Test with TranslationTransform XXX" << std::endl << std::endl;
int result = itkObjectToObjectMultiMetricv4TestRun(false);
if (result == EXIT_FAILURE)
{
std::cerr << "Failed test with translation transform. See message above." << std::endl;
return EXIT_FAILURE;
}
std::cout << std::endl << std::endl << "XXX Test with DisplacementFieldTransform XXX" << std::endl << std::endl;
result = itkObjectToObjectMultiMetricv4TestRun(true);
if (result == EXIT_FAILURE)
{
std::cerr << "Failed test with displacement field transform. See message above." << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}