void RadialMultishellToSingleshellImageFilter<TInputScalarType, TOutputScalarType> ::BeforeThreadedGenerateData() { // test whether BvalueMap contains all necessary information if(m_BValueMap.size() == 0) { itkWarningMacro(<< "No BValueMap given: create one using GradientDirectionContainer"); GradientDirectionContainerType::ConstIterator gdcit; for( gdcit = m_OriginalGradientDirections->Begin(); gdcit != m_OriginalGradientDirections->End(); ++gdcit) { double bValueKey = int(((m_OriginalBValue * gdcit.Value().two_norm() * gdcit.Value().two_norm())+7.5)/10)*10; m_BValueMap[bValueKey].push_back(gdcit.Index()); } }
void DiffusionMultiShellQballReconstructionImageFilter<T,TG,TO,L,NODF> ::SetGradientImage(const GradientDirectionContainerType *gradientDirection , const GradientImagesType *gradientImage , float bvalue) { m_BValue = bvalue; m_NumberOfBaselineImages = 0; this->m_GradientDirectionContainer = GradientDirectionContainerType::New(); for(GradientDirectionContainerType::ConstIterator it = gradientDirection->Begin(); it != gradientDirection->End(); it++) { this->m_GradientDirectionContainer->push_back(it.Value()); } if(m_BValueMap.size() == 0) { itkWarningMacro(<< "DiffusionMultiShellQballReconstructionImageFilter.cpp : no GradientIndexMapAvalible"); GradientDirectionContainerType::ConstIterator gdcit; for( gdcit = m_GradientDirectionContainer->Begin(); gdcit != m_GradientDirectionContainer->End(); ++gdcit) { double bValueKey = int(((m_BValue * gdcit.Value().two_norm() * gdcit.Value().two_norm())+7.5)/10)*10; m_BValueMap[bValueKey].push_back(gdcit.Index()); } }
void QmitkTensorReconstructionView::ItkTensorReconstruction(mitk::DataStorage::SetOfObjects::Pointer inImages) { try { itk::TimeProbe clock; int nrFiles = inImages->size(); if (!nrFiles) return; QString status; mitk::ProgressBar::GetInstance()->AddStepsToDo(nrFiles); mitk::DataStorage::SetOfObjects::const_iterator itemiter( inImages->begin() ); mitk::DataStorage::SetOfObjects::const_iterator itemiterend( inImages->end() ); std::vector<mitk::DataNode::Pointer> nodes; while ( itemiter != itemiterend ) // for all items { mitk::DiffusionImage<DiffusionPixelType>* vols = static_cast<mitk::DiffusionImage<DiffusionPixelType>*>( (*itemiter)->GetData()); std::string nodename; (*itemiter)->GetStringProperty("name", nodename); ++itemiter; // TENSOR RECONSTRUCTION clock.Start(); MITK_DEBUG << "Tensor reconstruction "; mitk::StatusBar::GetInstance()->DisplayText(status.sprintf("Tensor reconstruction for %s", nodename.c_str()).toAscii()); typedef itk::DiffusionTensor3DReconstructionImageFilter< DiffusionPixelType, DiffusionPixelType, TTensorPixelType > TensorReconstructionImageFilterType; TensorReconstructionImageFilterType::Pointer tensorReconstructionFilter = TensorReconstructionImageFilterType::New(); typedef mitk::DiffusionImage<DiffusionPixelType> DiffusionImageType; typedef DiffusionImageType::GradientDirectionContainerType GradientDirectionContainerType; GradientDirectionContainerType::Pointer gradientContainerCopy = GradientDirectionContainerType::New(); for(GradientDirectionContainerType::ConstIterator it = vols->GetDirections()->Begin(); it != vols->GetDirections()->End(); it++) { gradientContainerCopy->push_back(it.Value()); } tensorReconstructionFilter->SetGradientImage( gradientContainerCopy, vols->GetVectorImage() ); tensorReconstructionFilter->SetBValue(vols->GetB_Value()); tensorReconstructionFilter->SetThreshold( m_Controls->m_TensorReconstructionThreshold->value() ); tensorReconstructionFilter->Update(); clock.Stop(); MITK_DEBUG << "took " << clock.GetMeanTime() << "s."; // TENSORS TO DATATREE mitk::TensorImage::Pointer image = mitk::TensorImage::New(); typedef itk::Image<itk::DiffusionTensor3D<TTensorPixelType>, 3> TensorImageType; TensorImageType::Pointer tensorImage; tensorImage = tensorReconstructionFilter->GetOutput(); // Check the tensor for negative eigenvalues if(m_Controls->m_CheckNegativeEigenvalues->isChecked()) { typedef itk::ImageRegionIterator<TensorImageType> TensorImageIteratorType; TensorImageIteratorType tensorIt(tensorImage, tensorImage->GetRequestedRegion()); tensorIt.GoToBegin(); while(!tensorIt.IsAtEnd()) { typedef itk::DiffusionTensor3D<TTensorPixelType> TensorType; //typedef itk::Tensor<TTensorPixelType, 3> TensorType2; TensorType tensor = tensorIt.Get(); TensorType::EigenValuesArrayType ev; tensor.ComputeEigenValues(ev); for(unsigned int i=0; i<ev.Size(); i++) { if(ev[i] < 0.0) { tensor.Fill(0.0); tensorIt.Set(tensor); break; } } ++tensorIt; } } tensorImage->SetDirection( vols->GetVectorImage()->GetDirection() ); image->InitializeByItk( tensorImage.GetPointer() ); image->SetVolume( tensorReconstructionFilter->GetOutput()->GetBufferPointer() ); mitk::DataNode::Pointer node=mitk::DataNode::New(); node->SetData( image ); QString newname; newname = newname.append(nodename.c_str()); newname = newname.append("_dti"); SetDefaultNodeProperties(node, newname.toStdString()); nodes.push_back(node); mitk::ProgressBar::GetInstance()->Progress(); } std::vector<mitk::DataNode::Pointer>::iterator nodeIt; for(nodeIt = nodes.begin(); nodeIt != nodes.end(); ++nodeIt) GetDefaultDataStorage()->Add(*nodeIt); mitk::StatusBar::GetInstance()->DisplayText(status.sprintf("Finished Processing %d Files", nrFiles).toAscii()); m_MultiWidget->RequestUpdate(); } catch (itk::ExceptionObject &ex) { MITK_INFO << ex ; QMessageBox::information(0, "Reconstruction not possible:", ex.GetDescription()); return; } }
void QmitkTensorReconstructionView::TensorReconstructionWithCorr (mitk::DataStorage::SetOfObjects::Pointer inImages) { try { itk::TimeProbe clock; int nrFiles = inImages->size(); if (!nrFiles) return; QString status; mitk::ProgressBar::GetInstance()->AddStepsToDo(nrFiles); mitk::DataStorage::SetOfObjects::const_iterator itemiter( inImages->begin() ); mitk::DataStorage::SetOfObjects::const_iterator itemiterend( inImages->end() ); std::vector<mitk::DataNode::Pointer> nodes; while ( itemiter != itemiterend ) // for all items { typedef mitk::DiffusionImage<DiffusionPixelType> DiffusionImageType; typedef DiffusionImageType::GradientDirectionContainerType GradientDirectionContainerType; DiffusionImageType* vols = static_cast<DiffusionImageType*>((*itemiter)->GetData()); std::string nodename; (*itemiter)->GetStringProperty("name", nodename); ++itemiter; // TENSOR RECONSTRUCTION clock.Start(); MITK_INFO << "Tensor reconstruction with correction for negative eigenvalues"; mitk::StatusBar::GetInstance()->DisplayText(status.sprintf("Tensor reconstruction for %s", nodename.c_str()).toAscii()); typedef itk::TensorReconstructionWithEigenvalueCorrectionFilter< DiffusionPixelType, TTensorPixelType > ReconstructionFilter; float b0Threshold = m_Controls->m_TensorReconstructionThreshold->value(); GradientDirectionContainerType::Pointer gradientContainerCopy = GradientDirectionContainerType::New(); for(GradientDirectionContainerType::ConstIterator it = vols->GetDirections()->Begin(); it != vols->GetDirections()->End(); it++) { gradientContainerCopy->push_back(it.Value()); } ReconstructionFilter::Pointer reconFilter = ReconstructionFilter::New(); reconFilter->SetGradientImage( gradientContainerCopy, vols->GetVectorImage() ); reconFilter->SetBValue(vols->GetB_Value()); reconFilter->SetB0Threshold(b0Threshold); reconFilter->Update(); typedef itk::Image<itk::DiffusionTensor3D<TTensorPixelType>, 3> TensorImageType; TensorImageType::Pointer outputTensorImg = reconFilter->GetOutput(); typedef itk::ImageRegionIterator<TensorImageType> TensorImageIteratorType; TensorImageIteratorType tensorIt(outputTensorImg, outputTensorImg->GetRequestedRegion()); tensorIt.GoToBegin(); int negatives = 0; while(!tensorIt.IsAtEnd()) { typedef itk::DiffusionTensor3D<TTensorPixelType> TensorType; TensorType tensor = tensorIt.Get(); TensorType::EigenValuesArrayType ev; tensor.ComputeEigenValues(ev); for(unsigned int i=0; i<ev.Size(); i++) { if(ev[i] < 0.0) { tensor.Fill(0.0); tensorIt.Set(tensor); negatives++; break; } } ++tensorIt; } MITK_INFO << negatives << " tensors with negative eigenvalues" << std::endl; mitk::TensorImage::Pointer image = mitk::TensorImage::New(); image->InitializeByItk( outputTensorImg.GetPointer() ); image->SetVolume( outputTensorImg->GetBufferPointer() ); mitk::DataNode::Pointer node=mitk::DataNode::New(); node->SetData( image ); QString newname; newname = newname.append(nodename.c_str()); newname = newname.append("_dti_corrected"); SetDefaultNodeProperties(node, newname.toStdString()); nodes.push_back(node); // Corrected diffusion image // typedef itk::VectorImage<short, 3> ImageType; // ImageType::Pointer correctedVols = reconFilter->GetVectorImage(); // DiffusionImageType::Pointer correctedDiffusion = DiffusionImageType::New(); // correctedDiffusion->SetVectorImage(correctedVols); // correctedDiffusion->SetDirections(vols->GetDirections()); // correctedDiffusion->SetB_Value(vols->GetB_Value()); // correctedDiffusion->InitializeFromVectorImage(); // mitk::DataNode::Pointer diffNode = mitk::DataNode::New(); // diffNode->SetData( correctedDiffusion ); // QString diffname; // diffname = diffname.append(nodename.c_str()); // diffname = diffname.append("corrDiff"); // SetDefaultNodeProperties(diffNode, diffname.toStdString()); // nodes.push_back(diffNode); mitk::ProgressBar::GetInstance()->Progress(); } std::vector<mitk::DataNode::Pointer>::iterator nodeIt; for(nodeIt = nodes.begin(); nodeIt != nodes.end(); ++nodeIt) GetDefaultDataStorage()->Add(*nodeIt); mitk::StatusBar::GetInstance()->DisplayText(status.sprintf("Finished Processing %d Files", nrFiles).toAscii()); m_MultiWidget->RequestUpdate(); } catch (itk::ExceptionObject &ex) { MITK_INFO << ex ; QMessageBox::information(0, "Reconstruction not possible:", ex.GetDescription()); } }