void MutualInformationRegistration::updateRegistration() { if(!isReady()) return; convertVolumes(); //typedef itk::RegularStepGradientDescentOptimizer OptimizerType; typedef itk::VersorRigid3DTransformOptimizer OptimizerType; typedef OptimizerType::ScalesType OptimizerScalesType; typedef itk::LinearInterpolateImageFunction< InternalImageType, double > InterpolatorType; typedef itk::MattesMutualInformationImageToImageMetric< InternalImageType, InternalImageType > MetricType; typedef itk::MultiResolutionImageRegistrationMethod< InternalImageType, InternalImageType > RegistrationType; typedef itk::MultiResolutionPyramidImageFilter< InternalImageType, InternalImageType > FixedImagePyramidType; typedef itk::MultiResolutionPyramidImageFilter< InternalImageType, InternalImageType > MovingImagePyramidType; OptimizerType::Pointer optimizer = OptimizerType::New(); InterpolatorType::Pointer interpolator = InterpolatorType::New(); RegistrationType::Pointer registration = RegistrationType::New(); MetricType::Pointer metric = MetricType::New(); FixedImagePyramidType::Pointer fixedImagePyramid = FixedImagePyramidType::New(); MovingImagePyramidType::Pointer movingImagePyramid = MovingImagePyramidType::New(); registration->SetOptimizer(optimizer); registration->SetTransform(transform_); registration->SetInterpolator(interpolator); registration->SetMetric(metric); registration->SetFixedImagePyramid(fixedImagePyramid); registration->SetMovingImagePyramid(movingImagePyramid); OptimizerScalesType optimizerScales( transform_->GetNumberOfParameters() ); float rotScale = 1.0 / 1000.0f; optimizerScales[0] = 1.0f; optimizerScales[1] = 1.0f; optimizerScales[2] = 1.0f; optimizerScales[3] = rotScale; optimizerScales[4] = rotScale; optimizerScales[5] = rotScale; optimizer->SetScales( optimizerScales ); optimizer->SetMaximumStepLength(0.2); optimizer->SetMinimumStepLength(0.0001); InternalImageType::Pointer fixed = voreenToITK<float>(fixedVolumeFloat_); InternalImageType::Pointer moving = voreenToITK<float>(movingVolumeFloat_); registration->SetFixedImage(fixed); registration->SetMovingImage(moving); registration->SetFixedImageRegion( fixed->GetBufferedRegion() ); registration->SetInitialTransformParameters( transform_->GetParameters() ); metric->SetNumberOfHistogramBins(numHistogramBins_.get()); size_t numVoxels = hmul(fixedVolumeFloat_->getDimensions()); metric->SetNumberOfSpatialSamples(numVoxels * numSamples_.get()); metric->ReinitializeSeed( 76926294 ); //// Define whether to calculate the metric derivative by explicitly //// computing the derivatives of the joint PDF with respect to the Transform //// parameters, or doing it by progressively accumulating contributions from //// each bin in the joint PDF. metric->SetUseExplicitPDFDerivatives(explicitPDF_.get()); optimizer->SetNumberOfIterations(numIterations_.get()); optimizer->SetRelaxationFactor(relaxationFactor_.get()); // Create the Command observer and register it with the optimizer. CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New(); optimizer->AddObserver( itk::IterationEvent(), observer ); typedef RegistrationInterfaceCommand<RegistrationType> CommandType; CommandType::Pointer command = CommandType::New(); registration->AddObserver( itk::IterationEvent(), command ); registration->SetNumberOfLevels(numLevels_.get()); try { registration->StartRegistration(); std::cout << "Optimizer stop condition: " << registration->GetOptimizer()->GetStopConditionDescription() << std::endl; } catch( itk::ExceptionObject & err ) { std::cout << "ExceptionObject caught !" << std::endl; std::cout << err << std::endl; //return EXIT_FAILURE; } ParametersType finalParameters = registration->GetLastTransformParameters(); transform_->SetParameters(finalParameters); unsigned int numberOfIterations = optimizer->GetCurrentIteration(); double bestValue = optimizer->GetValue(); // Print out results std::cout << "Result = " << std::endl; std::cout << " Versor " << finalParameters[0] << " " << finalParameters[1] << " " << finalParameters[2] << std::endl; std::cout << " Translation " << finalParameters[1] << " " << finalParameters[4] << " " << finalParameters[5] << std::endl; std::cout << " Iterations = " << numberOfIterations << std::endl; std::cout << " Metric value = " << bestValue << std::endl; invalidate(INVALID_RESULT); }
void QAngioSubstractionExtension::computeAutomateSingleImage() { QApplication::setOverrideCursor(Qt::WaitCursor); const unsigned int Dimension = 2; typedef Volume::ItkPixelType PixelType; typedef itk::Image< PixelType, Dimension > FixedImageType; typedef itk::Image< PixelType, Dimension > MovingImageType; typedef float InternalPixelType; typedef itk::Image< InternalPixelType, Dimension > InternalImageType; typedef itk::TranslationTransform< double, Dimension > TransformType; typedef itk::GradientDescentOptimizer OptimizerType; typedef itk::LinearInterpolateImageFunction< InternalImageType, double > InterpolatorType; typedef itk::ImageRegistrationMethod< InternalImageType, InternalImageType > RegistrationType; typedef itk::MutualInformationImageToImageMetric< InternalImageType, InternalImageType > MetricType; TransformType::Pointer transform = TransformType::New(); OptimizerType::Pointer optimizer = OptimizerType::New(); InterpolatorType::Pointer interpolator = InterpolatorType::New(); RegistrationType::Pointer registration = RegistrationType::New(); registration->SetOptimizer(optimizer); registration->SetTransform(transform); registration->SetInterpolator(interpolator); MetricType::Pointer metric = MetricType::New(); registration->SetMetric(metric); metric->SetFixedImageStandardDeviation(0.4); metric->SetMovingImageStandardDeviation(0.4); metric->SetNumberOfSpatialSamples(50); typedef itk::ExtractImageFilter< Volume::ItkImageType, FixedImageType > FilterType; FilterType::Pointer extractFixedImageFilter = FilterType::New(); Volume::ItkImageType::RegionType inputRegion = m_mainVolume->getItkData()->GetLargestPossibleRegion(); Volume::ItkImageType::SizeType size = inputRegion.GetSize(); //Dividim la mida per dos per tal de quedar-nos només amb la part central // ja que si no ens registre el background size[0] = size[0] / 2; size[1] = size[1] / 2; size[2] = 0; Volume::ItkImageType::IndexType start = inputRegion.GetIndex(); const unsigned int sliceReference = m_imageSelectorSpinBox->value(); //comencem a un quart de la imatge start[0] = size[0] / 2; start[1] = size[1] / 2; start[2] = sliceReference; Volume::ItkImageType::RegionType desiredRegion; desiredRegion.SetSize(size); desiredRegion.SetIndex(start); extractFixedImageFilter->SetExtractionRegion(desiredRegion); extractFixedImageFilter->SetInput(m_mainVolume->getItkData()); extractFixedImageFilter->Update(); FilterType::Pointer extractMovingImageFilter = FilterType::New(); Volume::ItkImageType::IndexType startMoving = inputRegion.GetIndex(); const unsigned int sliceNumber = m_2DView_1->getViewer()->getCurrentSlice(); startMoving[0] = size[0] / 2; startMoving[1] = size[1] / 2; startMoving[2] = sliceNumber; Volume::ItkImageType::RegionType desiredMovingRegion; desiredMovingRegion.SetSize(size); desiredMovingRegion.SetIndex(startMoving); extractMovingImageFilter->SetExtractionRegion(desiredMovingRegion); extractMovingImageFilter->SetInput(m_mainVolume->getItkData()); extractMovingImageFilter->Update(); typedef itk::NormalizeImageFilter< FixedImageType, InternalImageType > FixedNormalizeFilterType; typedef itk::NormalizeImageFilter< MovingImageType, InternalImageType > MovingNormalizeFilterType; FixedNormalizeFilterType::Pointer fixedNormalizer = FixedNormalizeFilterType::New(); MovingNormalizeFilterType::Pointer movingNormalizer = MovingNormalizeFilterType::New(); typedef itk::DiscreteGaussianImageFilter< InternalImageType, InternalImageType > GaussianFilterType; GaussianFilterType::Pointer fixedSmoother = GaussianFilterType::New(); GaussianFilterType::Pointer movingSmoother = GaussianFilterType::New(); fixedSmoother->SetVariance(2.0); movingSmoother->SetVariance(2.0); fixedNormalizer->SetInput(extractFixedImageFilter->GetOutput()); movingNormalizer->SetInput(extractMovingImageFilter->GetOutput()); fixedSmoother->SetInput(fixedNormalizer->GetOutput()); movingSmoother->SetInput(movingNormalizer->GetOutput()); registration->SetFixedImage(fixedSmoother->GetOutput()); registration->SetMovingImage(movingSmoother->GetOutput()); fixedNormalizer->Update(); registration->SetFixedImageRegion( fixedNormalizer->GetOutput()->GetBufferedRegion()); typedef RegistrationType::ParametersType ParametersType; ParametersType initialParameters(transform->GetNumberOfParameters()); initialParameters[0] = 0.0; // Initial offset in mm along X initialParameters[1] = 0.0; // Initial offset in mm along Y registration->SetInitialTransformParameters(initialParameters); optimizer->SetLearningRate(20.0); optimizer->SetNumberOfIterations(200); optimizer->MaximizeOn(); try { registration->Update(); } catch(itk::ExceptionObject & err) { std::cout << "ExceptionObject caught !" << std::endl; std::cout << err << std::endl; return; } ParametersType finalParameters = registration->GetLastTransformParameters(); double TranslationAlongX = finalParameters[0]; double TranslationAlongY = finalParameters[1]; // Print out results // DEBUG_LOG(QString("Result = ")); DEBUG_LOG(QString(" Translation X = %1").arg(TranslationAlongX)); DEBUG_LOG(QString(" Translation Y = %1").arg(TranslationAlongY)); DEBUG_LOG(QString(" Iterations = %1").arg(optimizer->GetCurrentIteration())); DEBUG_LOG(QString(" Metric value = %1").arg(optimizer->GetValue())); double spacing[3]; m_mainVolume->getSpacing(spacing); DEBUG_LOG(QString(" Translation X (in px) = %1").arg(TranslationAlongX / spacing[0])); DEBUG_LOG(QString(" Translation Y (in px) = %1").arg(TranslationAlongY / spacing[1])); //Actualitzem les dades de la transdifference tool m_toolManager->triggerTool("TransDifferenceTool"); TransDifferenceTool* tdTool = static_cast<TransDifferenceTool*> (m_2DView_2->getViewer()->getToolProxy()->getTool("TransDifferenceTool")); if(m_tdToolData == 0){ m_tdToolData = static_cast<TransDifferenceToolData*> (tdTool->getToolData()); } if(m_tdToolData->getInputVolume() != m_mainVolume){ m_tdToolData->setInputVolume(m_mainVolume); } tdTool->setSingleDifferenceImage(TranslationAlongX / spacing[0],TranslationAlongY / spacing[1]); m_toolManager->triggerTool("SlicingTool"); /* typedef itk::Image< PixelType, Dimension > FixedImageType; typedef itk::Image< PixelType, Dimension > MovingImageType; typedef itk::TranslationTransform< double, Dimension > TransformType; typedef itk::RegularStepGradientDescentOptimizer OptimizerType; typedef itk::MattesMutualInformationImageToImageMetric< FixedImageType, MovingImageType > MetricType; typedef itk:: LinearInterpolateImageFunction< MovingImageType, double > InterpolatorType; typedef itk::ImageRegistrationMethod< FixedImageType, MovingImageType > RegistrationType; MetricType::Pointer metric = MetricType::New(); TransformType::Pointer transform = TransformType::New(); OptimizerType::Pointer optimizer = OptimizerType::New(); InterpolatorType::Pointer interpolator = InterpolatorType::New(); RegistrationType::Pointer registration = RegistrationType::New(); registration->SetMetric(metric); registration->SetOptimizer(optimizer); registration->SetTransform(transform); registration->SetInterpolator(interpolator); metric->SetNumberOfHistogramBins(50); metric->SetNumberOfSpatialSamples(10000); typedef itk::ExtractImageFilter< Volume::ItkImageType, FixedImageType > FilterType; FilterType::Pointer extractFixedImageFilter = FilterType::New(); Volume::ItkImageType::RegionType inputRegion = m_mainVolume->getItkData()->GetLargestPossibleRegion(); Volume::ItkImageType::SizeType size = inputRegion.GetSize(); //Dividim la mida per dos per tal de quedar-nos només amb la part central // ja que si no ens registre el background size[0] = size[0] / 2; size[1] = size[1] / 2; size[2] = 0; Volume::ItkImageType::IndexType start = inputRegion.GetIndex(); const unsigned int sliceReference = m_imageSelectorSpinBox->value(); //comencem a un quart de la imatge start[0] = size[0] / 2; start[1] = size[1] / 2; start[2] = sliceReference; Volume::ItkImageType::RegionType desiredRegion; desiredRegion.SetSize(size); desiredRegion.SetIndex(start); extractFixedImageFilter->SetExtractionRegion(desiredRegion); extractFixedImageFilter->SetInput(m_mainVolume->getItkData()); extractFixedImageFilter->Update(); FilterType::Pointer extractMovingImageFilter = FilterType::New(); Volume::ItkImageType::IndexType startMoving = inputRegion.GetIndex(); const unsigned int sliceNumber = m_2DView_1->getViewer()->getCurrentSlice(); startMoving[0] = size[0] / 2; startMoving[1] = size[1] / 2; startMoving[2] = sliceNumber; Volume::ItkImageType::RegionType desiredMovingRegion; desiredMovingRegion.SetSize(size); desiredMovingRegion.SetIndex(startMoving); extractMovingImageFilter->SetExtractionRegion(desiredMovingRegion); extractMovingImageFilter->SetInput(m_mainVolume->getItkData()); extractMovingImageFilter->Update(); registration->SetFixedImage(extractFixedImageFilter->GetOutput()); registration->SetMovingImage(extractMovingImageFilter->GetOutput()); typedef RegistrationType::ParametersType ParametersType; ParametersType initialParameters(transform->GetNumberOfParameters()); //Potser seria millor posar la transformada que té actualment initialParameters[0] = 0.0; // Initial offset in mm along X initialParameters[1] = 0.0; // Initial offset in mm along Y registration->SetInitialTransformParameters(initialParameters); optimizer->SetMaximumStepLength(4.00); optimizer->SetMinimumStepLength(0.005); optimizer->SetNumberOfIterations(200); try { registration->StartRegistration(); } catch(itk::ExceptionObject & err) { DEBUG_LOG(QString("ExceptionObject caught !")); std::cout<<err<<std::endl; return; } ParametersType finalParameters = registration->GetLastTransformParameters(); const double TranslationAlongX = finalParameters[0]; const double TranslationAlongY = finalParameters[1]; const unsigned int numberOfIterations = optimizer->GetCurrentIteration(); const double bestValue = optimizer->GetValue(); DEBUG_LOG(QString("Result = ")); DEBUG_LOG(QString(" Translation X = %1").arg(TranslationAlongX)); DEBUG_LOG(QString(" Translation Y = %1").arg(TranslationAlongY)); DEBUG_LOG(QString(" Iterations = %1").arg(numberOfIterations)); DEBUG_LOG(QString(" Metric value = %1").arg(bestValue)); typedef unsigned char OutputPixelType; typedef itk::Image< OutputPixelType, Dimension > OutputImageType; typedef itk::RescaleIntensityImageFilter< FixedImageType, FixedImageType > RescaleFilterType; typedef itk::ResampleImageFilter< FixedImageType, FixedImageType > ResampleFilterType; typedef itk::CastImageFilter< FixedImageType, OutputImageType > CastFilterType; typedef itk::ImageFileWriter< OutputImageType > WriterType; WriterType::Pointer writer = WriterType::New(); CastFilterType::Pointer caster = CastFilterType::New(); ResampleFilterType::Pointer resample = ResampleFilterType::New(); RescaleFilterType::Pointer rescaler = RescaleFilterType::New(); rescaler->SetOutputMinimum(0); rescaler->SetOutputMaximum(255); TransformType::Pointer finalTransform = TransformType::New(); finalTransform->SetParameters(finalParameters); resample->SetTransform(finalTransform); resample->SetSize(extractMovingImageFilter->GetOutput()->GetLargestPossibleRegion().GetSize()); resample->SetOutputOrigin(extractMovingImageFilter->GetOutput()->GetOrigin()); resample->SetOutputSpacing(extractMovingImageFilter->GetOutput()->GetSpacing()); resample->SetDefaultPixelValue(100); writer->SetFileName("prova.jpg"); rescaler->SetInput(extractMovingImageFilter->GetOutput()); resample->SetInput(rescaler->GetOutput()); caster->SetInput(resample->GetOutput()); writer->SetInput(caster->GetOutput()); writer->Update(); */ QApplication::restoreOverrideCursor(); }