/*========================================================================= * * 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 "itkImageFileReader.h" #include "itkImageFileWriter.h" #include "itkImageRegistrationMethodv4.h" #include "itkSyNImageRegistrationMethod.h" #include "itkAffineTransform.h" #include "itkANTSNeighborhoodCorrelationImageToImageMetricv4.h" #include "itkCompositeTransform.h" #include "itkDisplacementFieldTransformParametersAdaptor.h" #include "itkVector.h" #include "itkTestingMacros.h" template class CommandIterationUpdate : public itk::Command { public: using Self = CommandIterationUpdate; using Superclass = itk::Command; using Pointer = itk::SmartPointer; itkNewMacro(Self); using FixedImageType = typename TFilter::FixedImageType; static constexpr unsigned int ImageDimension = FixedImageType::ImageDimension; /** ImageDimension constants */ using ShrinkFilterType = itk::ShrinkImageFilter; using RealType = typename TFilter::OutputTransformType::ScalarType; using DisplacementFieldTransformType = itk::DisplacementFieldTransform; using DisplacementFieldType = typename DisplacementFieldTransformType::DisplacementFieldType; protected: CommandIterationUpdate() = default; public: void Execute(itk::Object * caller, const itk::EventObject & event) override { Execute((const itk::Object *)caller, event); } void Execute(const itk::Object * object, const itk::EventObject & event) override { const auto * filter = dynamic_cast(object); if (typeid(event) != typeid(itk::IterationEvent)) { return; } unsigned int currentLevel = filter->GetCurrentLevel(); typename TFilter::ShrinkFactorsPerDimensionContainerType shrinkFactors = filter->GetShrinkFactorsPerDimension(currentLevel); typename TFilter::SmoothingSigmasArrayType smoothingSigmas = filter->GetSmoothingSigmasPerLevel(); typename TFilter::TransformParametersAdaptorsContainerType adaptors = filter->GetTransformParametersAdaptorsPerLevel(); std::cout << " Current level = " << currentLevel << std::endl; std::cout << " shrink factor = " << shrinkFactors << std::endl; std::cout << " smoothing sigma = " << smoothingSigmas[currentLevel] << std::endl; std::cout << " required fixed parameters = " << adaptors[currentLevel]->GetRequiredFixedParameters() << std::endl; /* testing "itkGetConstObjectMacro" at each iteration */ typename ShrinkFilterType::Pointer shrinkFilter = ShrinkFilterType::New(); shrinkFilter->SetShrinkFactors(shrinkFactors); shrinkFilter->SetInput(filter->GetFixedImage()); shrinkFilter->Update(); const typename FixedImageType::SizeType ImageSize = shrinkFilter->GetOutput()->GetBufferedRegion().GetSize(); const typename DisplacementFieldType::SizeType FixedDisplacementFieldSize = filter->GetFixedToMiddleTransform()->GetDisplacementField()->GetBufferedRegion().GetSize(); const typename DisplacementFieldType::SizeType MovingDisplacementFieldSize = filter->GetMovingToMiddleTransform()->GetDisplacementField()->GetBufferedRegion().GetSize(); if ((FixedDisplacementFieldSize == ImageSize) && (MovingDisplacementFieldSize == ImageSize)) { std::cout << " *Filter returns its internal transforms properly*" << std::endl; } else { itkExceptionMacro("Internal transforms should be consistent with input image size at each iteration. " << "Image size = " << ImageSize << ". Fixed field size = " << FixedDisplacementFieldSize << ". Moving field size = " << MovingDisplacementFieldSize << "."); } } }; template int PerformDisplacementFieldImageRegistration(int itkNotUsed(argc), char * argv[]) { const unsigned int ImageDimension = TDimension; using PixelType = double; using FixedImageType = itk::Image; using MovingImageType = itk::Image; using ImageReaderType = itk::ImageFileReader; typename ImageReaderType::Pointer fixedImageReader = ImageReaderType::New(); fixedImageReader->SetFileName(argv[2]); fixedImageReader->Update(); typename FixedImageType::Pointer fixedImage = fixedImageReader->GetOutput(); fixedImage->Update(); fixedImage->DisconnectPipeline(); typename ImageReaderType::Pointer movingImageReader = ImageReaderType::New(); movingImageReader->SetFileName(argv[3]); movingImageReader->Update(); typename MovingImageType::Pointer movingImage = movingImageReader->GetOutput(); movingImage->Update(); movingImage->DisconnectPipeline(); using AffineTransformType = itk::AffineTransform; using AffineRegistrationType = itk::ImageRegistrationMethodv4; typename AffineRegistrationType::Pointer affineSimple = AffineRegistrationType::New(); affineSimple->SetFixedImage(fixedImage); affineSimple->SetMovingImage(movingImage); // Shrink the virtual domain by specified factors for each level. See documentation // for the itkShrinkImageFilter for more detailed behavior. typename AffineRegistrationType::ShrinkFactorsArrayType affineShrinkFactorsPerLevel; affineShrinkFactorsPerLevel.SetSize(3); affineShrinkFactorsPerLevel[0] = 4; affineShrinkFactorsPerLevel[1] = 4; affineShrinkFactorsPerLevel[2] = 4; affineSimple->SetShrinkFactorsPerLevel(affineShrinkFactorsPerLevel); // Set the number of iterations using GradientDescentOptimizerv4Type = itk::GradientDescentOptimizerv4; auto * optimizer = dynamic_cast(affineSimple->GetModifiableOptimizer()); ITK_TEST_EXPECT_TRUE(optimizer != nullptr); #ifdef NDEBUG optimizer->SetNumberOfIterations(100); #else optimizer->SetNumberOfIterations(1); #endif std::cout << "Affine transform" << std::endl; ITK_TRY_EXPECT_NO_EXCEPTION(affineSimple->Update()); // // Now do the displacement field transform with gaussian smoothing using // the composite transform. // using RealType = typename AffineRegistrationType::RealType; using CompositeTransformType = itk::CompositeTransform; typename CompositeTransformType::Pointer compositeTransform = CompositeTransformType::New(); compositeTransform->AddTransform(affineSimple->GetModifiableTransform()); using AffineResampleFilterType = itk::ResampleImageFilter; typename AffineResampleFilterType::Pointer affineResampler = AffineResampleFilterType::New(); affineResampler->SetTransform(compositeTransform); affineResampler->SetInput(movingImage); affineResampler->SetSize(fixedImage->GetBufferedRegion().GetSize()); affineResampler->SetOutputOrigin(fixedImage->GetOrigin()); affineResampler->SetOutputSpacing(fixedImage->GetSpacing()); affineResampler->SetOutputDirection(fixedImage->GetDirection()); affineResampler->SetDefaultPixelValue(0); affineResampler->Update(); std::string affineMovingImageFileName = std::string(argv[4]) + std::string("MovingImageAfterAffineTransform.nii.gz"); using AffineWriterType = itk::ImageFileWriter; typename AffineWriterType::Pointer affineWriter = AffineWriterType::New(); affineWriter->SetFileName(affineMovingImageFileName.c_str()); affineWriter->SetInput(affineResampler->GetOutput()); affineWriter->Update(); using VectorType = itk::Vector; VectorType zeroVector(0.0); // Create the SyN deformable registration method using DisplacementFieldType = itk::Image; typename DisplacementFieldType::Pointer displacementField = DisplacementFieldType::New(); displacementField->CopyInformation(fixedImage); displacementField->SetRegions(fixedImage->GetBufferedRegion()); displacementField->Allocate(); displacementField->FillBuffer(zeroVector); typename DisplacementFieldType::Pointer inverseDisplacementField = DisplacementFieldType::New(); inverseDisplacementField->CopyInformation(fixedImage); inverseDisplacementField->SetRegions(fixedImage->GetBufferedRegion()); inverseDisplacementField->Allocate(); inverseDisplacementField->FillBuffer(zeroVector); using DisplacementFieldRegistrationType = itk::SyNImageRegistrationMethod; typename DisplacementFieldRegistrationType::Pointer displacementFieldRegistration = DisplacementFieldRegistrationType::New(); using OutputTransformType = typename DisplacementFieldRegistrationType::OutputTransformType; typename OutputTransformType::Pointer outputTransform = OutputTransformType::New(); outputTransform->SetDisplacementField(displacementField); outputTransform->SetInverseDisplacementField(inverseDisplacementField); displacementFieldRegistration->SetInitialTransform(outputTransform); displacementFieldRegistration->InPlaceOn(); // Test member functions displacementFieldRegistration->SetDownsampleImagesForMetricDerivatives(false); if (displacementFieldRegistration->GetDownsampleImagesForMetricDerivatives() != false) { return EXIT_FAILURE; } displacementFieldRegistration->SetDownsampleImagesForMetricDerivatives(true); if (displacementFieldRegistration->GetDownsampleImagesForMetricDerivatives() != true) { return EXIT_FAILURE; } displacementFieldRegistration->SetAverageMidPointGradients(false); if (displacementFieldRegistration->GetAverageMidPointGradients() != false) { return EXIT_FAILURE; } displacementFieldRegistration->SetAverageMidPointGradients(true); if (displacementFieldRegistration->GetAverageMidPointGradients() != true) { return EXIT_FAILURE; } // Create the transform adaptors using DisplacementFieldTransformAdaptorType = itk::DisplacementFieldTransformParametersAdaptor; typename DisplacementFieldRegistrationType::TransformParametersAdaptorsContainerType adaptors; // Create the transform adaptors // For the gaussian displacement field, the specified variances are in image spacing terms // and, in normal practice, we typically don't change these values at each level. However, // if the user wishes to add that option, they can use the class // GaussianSmoothingOnUpdateDisplacementFieldTransformAdaptor unsigned int numberOfLevels = 3; typename DisplacementFieldRegistrationType::NumberOfIterationsArrayType numberOfIterationsPerLevel; numberOfIterationsPerLevel.SetSize(3); #ifdef NDEBUG numberOfIterationsPerLevel[0] = std::stoi(argv[5]); numberOfIterationsPerLevel[1] = 2; numberOfIterationsPerLevel[2] = 1; #else numberOfIterationsPerLevel[0] = 1; numberOfIterationsPerLevel[1] = 1; numberOfIterationsPerLevel[2] = 1; #endif RealType varianceForUpdateField = 1.75; RealType varianceForTotalField = 0.5; typename DisplacementFieldRegistrationType::ShrinkFactorsArrayType shrinkFactorsPerLevel; shrinkFactorsPerLevel.SetSize(3); shrinkFactorsPerLevel[0] = 3; shrinkFactorsPerLevel[1] = 2; shrinkFactorsPerLevel[2] = 1; typename DisplacementFieldRegistrationType::SmoothingSigmasArrayType smoothingSigmasPerLevel; smoothingSigmasPerLevel.SetSize(3); smoothingSigmasPerLevel[0] = 2; smoothingSigmasPerLevel[1] = 1; smoothingSigmasPerLevel[2] = 0; for (unsigned int level = 0; level < numberOfLevels; level++) { // We use the shrink image filter to calculate the fixed parameters of the virtual // domain at each level. To speed up calculation and avoid unnecessary memory // usage, we could calculate these fixed parameters directly. using ShrinkFilterType = itk::ShrinkImageFilter; typename ShrinkFilterType::Pointer shrinkFilter = ShrinkFilterType::New(); shrinkFilter->SetShrinkFactors(shrinkFactorsPerLevel[level]); shrinkFilter->SetInput(displacementField); shrinkFilter->Update(); typename DisplacementFieldTransformAdaptorType::Pointer fieldTransformAdaptor = DisplacementFieldTransformAdaptorType::New(); fieldTransformAdaptor->SetRequiredSpacing(shrinkFilter->GetOutput()->GetSpacing()); fieldTransformAdaptor->SetRequiredSize(shrinkFilter->GetOutput()->GetBufferedRegion().GetSize()); fieldTransformAdaptor->SetRequiredDirection(shrinkFilter->GetOutput()->GetDirection()); fieldTransformAdaptor->SetRequiredOrigin(shrinkFilter->GetOutput()->GetOrigin()); fieldTransformAdaptor->SetTransform(outputTransform); adaptors.push_back(fieldTransformAdaptor); } using CorrelationMetricType = itk::ANTSNeighborhoodCorrelationImageToImageMetricv4; typename CorrelationMetricType::Pointer correlationMetric = CorrelationMetricType::New(); typename CorrelationMetricType::RadiusType radius; radius.Fill(4); correlationMetric->SetRadius(radius); correlationMetric->SetUseMovingImageGradientFilter(false); correlationMetric->SetUseFixedImageGradientFilter(false); displacementFieldRegistration->SetFixedImage(fixedImage); displacementFieldRegistration->SetMovingImage(movingImage); displacementFieldRegistration->SetNumberOfLevels(3); displacementFieldRegistration->SetMovingInitialTransform(compositeTransform); displacementFieldRegistration->SetShrinkFactorsPerLevel(shrinkFactorsPerLevel); displacementFieldRegistration->SetSmoothingSigmasPerLevel(smoothingSigmasPerLevel); displacementFieldRegistration->SetMetric(correlationMetric); const typename DisplacementFieldRegistrationType::RealType local_epsilon = itk::NumericTraits::epsilon(); const typename DisplacementFieldRegistrationType::RealType local_LearningRate = std::stod(argv[6]); displacementFieldRegistration->SetLearningRate(local_LearningRate); if (displacementFieldRegistration->GetLearningRate() - local_LearningRate > local_epsilon) { return EXIT_FAILURE; } displacementFieldRegistration->SetNumberOfIterationsPerLevel(numberOfIterationsPerLevel); if (displacementFieldRegistration->GetNumberOfIterationsPerLevel() != numberOfIterationsPerLevel) { return EXIT_FAILURE; } displacementFieldRegistration->SetTransformParametersAdaptorsPerLevel(adaptors); displacementFieldRegistration->SetGaussianSmoothingVarianceForTheUpdateField(varianceForUpdateField); if (displacementFieldRegistration->GetGaussianSmoothingVarianceForTheUpdateField() - varianceForUpdateField > local_epsilon) { return EXIT_FAILURE; } displacementFieldRegistration->SetGaussianSmoothingVarianceForTheTotalField(varianceForTotalField); if (displacementFieldRegistration->GetGaussianSmoothingVarianceForTheTotalField() - varianceForTotalField > local_epsilon) { return EXIT_FAILURE; } const typename DisplacementFieldRegistrationType::RealType local_ConvergenceThreshold = 1.0e-6; displacementFieldRegistration->SetConvergenceThreshold(local_ConvergenceThreshold); if (displacementFieldRegistration->GetConvergenceThreshold() - local_ConvergenceThreshold > local_epsilon) { return EXIT_FAILURE; } constexpr unsigned int local_ConvergenceWindowSize = 10; displacementFieldRegistration->SetConvergenceWindowSize(local_ConvergenceWindowSize); if (displacementFieldRegistration->GetConvergenceWindowSize() != local_ConvergenceWindowSize) { return EXIT_FAILURE; } using DisplacementFieldCommandType = CommandIterationUpdate; typename DisplacementFieldCommandType::Pointer DisplacementFieldObserver = DisplacementFieldCommandType::New(); displacementFieldRegistration->AddObserver(itk::IterationEvent(), DisplacementFieldObserver); try { std::cout << "SyN registration" << std::endl; displacementFieldRegistration->Update(); } catch (const itk::ExceptionObject & e) { std::cerr << "Exception caught: " << e << std::endl; return EXIT_FAILURE; } compositeTransform->AddTransform(outputTransform); using ResampleFilterType = itk::ResampleImageFilter; typename ResampleFilterType::Pointer resampler = ResampleFilterType::New(); resampler->SetTransform(compositeTransform); resampler->SetInput(movingImage); resampler->SetSize(fixedImage->GetBufferedRegion().GetSize()); resampler->SetOutputOrigin(fixedImage->GetOrigin()); resampler->SetOutputSpacing(fixedImage->GetSpacing()); resampler->SetOutputDirection(fixedImage->GetDirection()); resampler->SetDefaultPixelValue(0); resampler->Update(); std::string warpedMovingImageFileName = std::string(argv[4]) + std::string("MovingImageAfterSyN.nii.gz"); using WriterType = itk::ImageFileWriter; typename WriterType::Pointer writer = WriterType::New(); writer->SetFileName(warpedMovingImageFileName.c_str()); writer->SetInput(resampler->GetOutput()); writer->Update(); using InverseResampleFilterType = itk::ResampleImageFilter; typename InverseResampleFilterType::Pointer inverseResampler = ResampleFilterType::New(); inverseResampler->SetTransform(compositeTransform->GetInverseTransform()); inverseResampler->SetInput(fixedImage); inverseResampler->SetSize(movingImage->GetBufferedRegion().GetSize()); inverseResampler->SetOutputOrigin(movingImage->GetOrigin()); inverseResampler->SetOutputSpacing(movingImage->GetSpacing()); inverseResampler->SetOutputDirection(movingImage->GetDirection()); inverseResampler->SetDefaultPixelValue(0); inverseResampler->Update(); std::string inverseWarpedFixedImageFileName = std::string(argv[4]) + std::string("InverseWarpedFixedImage.nii.gz"); using InverseWriterType = itk::ImageFileWriter; typename InverseWriterType::Pointer inverseWriter = InverseWriterType::New(); inverseWriter->SetFileName(inverseWarpedFixedImageFileName.c_str()); inverseWriter->SetInput(inverseResampler->GetOutput()); inverseWriter->Update(); std::string displacementFieldFileName = std::string(argv[4]) + std::string("DisplacementField.nii.gz"); using DisplacementFieldWriterType = itk::ImageFileWriter; typename DisplacementFieldWriterType::Pointer displacementFieldWriter = DisplacementFieldWriterType::New(); displacementFieldWriter->SetFileName(displacementFieldFileName.c_str()); displacementFieldWriter->SetInput(outputTransform->GetDisplacementField()); displacementFieldWriter->Update(); return EXIT_SUCCESS; } int itkSyNImageRegistrationTest(int argc, char * argv[]) { if (argc < 5) { std::cout << itkNameOfTestExecutableMacro(argv) << " imageDimension fixedImage movingImage outputPrefix numberOfDeformableIterations learningRate" << std::endl; return EXIT_FAILURE; } // Exercise the objet's basic methods outside the templated test helper to // avoid the Superclass name not being found. constexpr unsigned int ImageDimension = 2; using PixelType = double; using FixedImageType = itk::Image; using MovingImageType = itk::Image; using DisplacementFieldRegistrationType = itk::SyNImageRegistrationMethod; typename DisplacementFieldRegistrationType::Pointer displacementFieldRegistration = DisplacementFieldRegistrationType::New(); ITK_EXERCISE_BASIC_OBJECT_METHODS( displacementFieldRegistration, SyNImageRegistrationMethod, ImageRegistrationMethodv4); switch (std::stoi(argv[1])) { case 2: PerformDisplacementFieldImageRegistration<2>(argc, argv); break; case 3: PerformDisplacementFieldImageRegistration<3>(argc, argv); break; default: std::cerr << "Unsupported dimension" << std::endl; return EXIT_FAILURE; } std::cout << "Test finished." << std::endl; return EXIT_SUCCESS; }