diff --git a/Modules/Bundles/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.cpp b/Modules/Bundles/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.cpp index 026df14322..e11a069779 100644 --- a/Modules/Bundles/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.cpp +++ b/Modules/Bundles/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.cpp @@ -1,847 +1,956 @@ /*========================================================================= Program: Medical Imaging & Interaction Toolkit Module: $RCSfile$ Language: C++ Date: $Date: 2009-05-28 17:19:30 +0200 (Do, 28 Mai 2009) $ Version: $Revision: 17495 $ Copyright (c) German Cancer Research Center, Division of Medical and Biological Informatics. All rights reserved. See MITKCopyright.txt or http://www.mitk.org/copyright.html for details. This software is distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the above copyright notices for more information. =========================================================================*/ #include "QmitkTensorReconstructionView.h" #include "mitkDiffusionImagingConfigure.h" // qt includes #include // itk includes #include "itkTimeProbe.h" //#include "itkTensor.h" // mitk includes #include "mitkProgressBar.h" #include "mitkStatusBar.h" #include "mitkNodePredicateDataType.h" #include "QmitkDataStorageComboBox.h" #include "QmitkStdMultiWidget.h" #include "mitkTeemDiffusionTensor3DReconstructionImageFilter.h" #include "itkDiffusionTensor3DReconstructionImageFilter.h" #include "itkTensorImageToDiffusionImageFilter.h" #include "itkPointShell.h" #include "itkVector.h" #include "mitkProperties.h" #include "mitkDataNodeObject.h" #include "mitkOdfNormalizationMethodProperty.h" #include "mitkOdfScaleByProperty.h" #include "mitkDiffusionImageMapper.h" #include "berryIStructuredSelection.h" #include "berryIWorkbenchWindow.h" #include "berryISelectionService.h" #include const std::string QmitkTensorReconstructionView::VIEW_ID = "org.mitk.views.tensorreconstruction"; #define DI_INFO MITK_INFO("DiffusionImaging") typedef float TTensorPixelType; using namespace berry; struct TrSelListener : ISelectionListener { berryObjectMacro(TrSelListener); TrSelListener(QmitkTensorReconstructionView* view) { m_View = view; } void DoSelectionChanged(ISelection::ConstPointer selection) { // if(!m_View->IsVisible()) // return; // save current selection in member variable m_View->m_CurrentSelection = selection.Cast(); // do something with the selected items if(m_View->m_CurrentSelection) { bool foundDwiVolume = false; bool foundTensorVolume = false; // iterate selection for (IStructuredSelection::iterator i = m_View->m_CurrentSelection->Begin(); i != m_View->m_CurrentSelection->End(); ++i) { // extract datatree node if (mitk::DataNodeObject::Pointer nodeObj = i->Cast()) { mitk::DataNode::Pointer node = nodeObj->GetDataNode(); // only look at interesting types if(QString("DiffusionImage").compare(node->GetData()->GetNameOfClass())==0) { foundDwiVolume = true; } // only look at interesting types if(QString("TensorImage").compare(node->GetData()->GetNameOfClass())==0) { foundTensorVolume = true; } } } m_View->m_Controls->m_ItkReconstruction->setEnabled(foundDwiVolume); m_View->m_Controls->m_TeemReconstruction->setEnabled(foundDwiVolume); m_View->m_Controls->m_TensorsToDWIButton->setEnabled(foundTensorVolume); m_View->m_Controls->m_TensorsToQbiButton->setEnabled(foundTensorVolume); + m_View->m_Controls->m_ResidualButton->setEnabled(foundDwiVolume && foundTensorVolume); + } } void SelectionChanged(IWorkbenchPart::Pointer part, ISelection::ConstPointer selection) { // check, if selection comes from datamanager if (part) { QString partname(part->GetPartName().c_str()); if(partname.compare("Datamanager")==0) { // apply selection DoSelectionChanged(selection); } } } QmitkTensorReconstructionView* m_View; }; QmitkTensorReconstructionView::QmitkTensorReconstructionView() : QmitkFunctionality(), m_Controls(NULL), m_MultiWidget(NULL) { } QmitkTensorReconstructionView::QmitkTensorReconstructionView(const QmitkTensorReconstructionView& other) { Q_UNUSED(other) throw std::runtime_error("Copy constructor not implemented"); } QmitkTensorReconstructionView::~QmitkTensorReconstructionView() { this->GetSite()->GetWorkbenchWindow()->GetSelectionService()->RemovePostSelectionListener(/*"org.mitk.views.datamanager",*/ m_SelListener); } void QmitkTensorReconstructionView::CreateQtPartControl(QWidget *parent) { if (!m_Controls) { // create GUI widgets m_Controls = new Ui::QmitkTensorReconstructionViewControls; m_Controls->setupUi(parent); this->CreateConnections(); QStringList items; items << "LLS (Linear Least Squares)" << "MLE (Maximum Likelihood)" << "NLS (Nonlinear Least Squares)" << "WLS (Weighted Least Squares)"; m_Controls->m_TensorEstimationTeemEstimationMethodCombo->addItems(items); m_Controls->m_TensorEstimationTeemEstimationMethodCombo->setCurrentIndex(0); m_Controls->m_TensorEstimationManualThreashold->setChecked(false); m_Controls->m_TensorEstimationTeemSigmaEdit->setText("NaN"); m_Controls->m_TensorEstimationTeemNumItsSpin->setValue(1); m_Controls->m_TensorEstimationTeemFuzzyEdit->setText("0.0"); m_Controls->m_TensorEstimationTeemMinValEdit->setText("1.0"); m_Controls->m_TensorEstimationTeemNumItsLabel_2->setEnabled(true); m_Controls->m_TensorEstimationTeemNumItsSpin->setEnabled(true); m_Controls->m_TensorsToDWIBValueEdit->setText("1000"); Advanced1CheckboxClicked(); Advanced2CheckboxClicked(); TeemCheckboxClicked(); #ifndef DIFFUSION_IMAGING_EXTENDED m_Controls->m_TeemToggle->setVisible(false); #endif // define data type for combobox //m_Controls->m_ImageSelector->SetDataStorage( this->GetDefaultDataStorage() ); //m_Controls->m_ImageSelector->SetPredicate( mitk::NodePredicateDataType::New("DiffusionImage") ); } m_SelListener = berry::ISelectionListener::Pointer(new TrSelListener(this)); this->GetSite()->GetWorkbenchWindow()->GetSelectionService()->AddPostSelectionListener(/*"org.mitk.views.datamanager",*/ m_SelListener); berry::ISelection::ConstPointer sel( this->GetSite()->GetWorkbenchWindow()->GetSelectionService()->GetSelection("org.mitk.views.datamanager")); m_CurrentSelection = sel.Cast(); m_SelListener.Cast()->DoSelectionChanged(sel); } void QmitkTensorReconstructionView::StdMultiWidgetAvailable (QmitkStdMultiWidget &stdMultiWidget) { berry::ISelection::ConstPointer sel( this->GetSite()->GetWorkbenchWindow()->GetSelectionService()->GetSelection("org.mitk.views.datamanager")); m_CurrentSelection = sel.Cast(); m_SelListener.Cast()->DoSelectionChanged(sel); m_MultiWidget = &stdMultiWidget; } void QmitkTensorReconstructionView::StdMultiWidgetNotAvailable() { m_MultiWidget = NULL; } void QmitkTensorReconstructionView::CreateConnections() { if ( m_Controls ) { connect( (QObject*)(m_Controls->m_TeemToggle), SIGNAL(clicked()), this, SLOT(TeemCheckboxClicked()) ); connect( (QObject*)(m_Controls->m_ItkReconstruction), SIGNAL(clicked()), this, SLOT(ItkReconstruction()) ); connect( (QObject*)(m_Controls->m_TeemReconstruction), SIGNAL(clicked()), this, SLOT(TeemReconstruction()) ); connect( (QObject*)(m_Controls->m_TensorEstimationTeemEstimationMethodCombo), SIGNAL(currentIndexChanged(int)), this, SLOT(MethodChoosen(int)) ); connect( (QObject*)(m_Controls->m_Advanced1), SIGNAL(clicked()), this, SLOT(Advanced1CheckboxClicked()) ); connect( (QObject*)(m_Controls->m_Advanced2), SIGNAL(clicked()), this, SLOT(Advanced2CheckboxClicked()) ); connect( (QObject*)(m_Controls->m_TensorEstimationManualThreashold), SIGNAL(clicked()), this, SLOT(ManualThresholdClicked()) ); connect( (QObject*)(m_Controls->m_TensorsToDWIButton), SIGNAL(clicked()), this, SLOT(TensorsToDWI()) ); connect( (QObject*)(m_Controls->m_TensorsToQbiButton), SIGNAL(clicked()), this, SLOT(TensorsToQbi()) ); + connect( (QObject*)(m_Controls->m_ResidualButton), SIGNAL(clicked()), this, SLOT(ResidualCalculation()) ); } } void QmitkTensorReconstructionView::TeemCheckboxClicked() { m_Controls->groupBox_3->setVisible(m_Controls-> m_TeemToggle->isChecked()); } void QmitkTensorReconstructionView::Advanced1CheckboxClicked() { bool check = m_Controls-> m_Advanced1->isChecked(); m_Controls->frame->setVisible(check); } void QmitkTensorReconstructionView::Advanced2CheckboxClicked() { bool check = m_Controls-> m_Advanced2->isChecked(); m_Controls->frame_2->setVisible(check); } void QmitkTensorReconstructionView::ManualThresholdClicked() { m_Controls->m_TensorReconstructionThreasholdEdit_2->setEnabled( m_Controls->m_TensorEstimationManualThreashold->isChecked()); } void QmitkTensorReconstructionView::Activated() { QmitkFunctionality::Activated(); } void QmitkTensorReconstructionView::Deactivated() { QmitkFunctionality::Deactivated(); } void QmitkTensorReconstructionView::MethodChoosen(int method) { m_Controls->m_TensorEstimationTeemNumItsLabel_2->setEnabled(method==3); m_Controls->m_TensorEstimationTeemNumItsSpin->setEnabled(method==3); } +void QmitkTensorReconstructionView::ResidualCalculation() +{ + // Extract dwi and dti from current selection + // In case of multiple selections, take the first one, since taking all combinations is not meaningful + if(m_CurrentSelection) + { + mitk::DataStorage::SetOfObjects::Pointer set = + mitk::DataStorage::SetOfObjects::New(); + + mitk::DiffusionImage::Pointer diffImage + = mitk::DiffusionImage::New(); + + typedef float TTensorPixelType; + typedef itk::DiffusionTensor3D< TTensorPixelType > TensorPixelType; + typedef itk::Image< TensorPixelType, 3 > TensorImageType; + + TensorImageType::Pointer tensorImage; + + std::string nodename; + + + for (IStructuredSelection::iterator i = m_CurrentSelection->Begin(); + i != m_CurrentSelection->End(); + ++i) + { + + if (mitk::DataNodeObject::Pointer nodeObj = i->Cast()) + { + mitk::DataNode::Pointer node = nodeObj->GetDataNode(); + if(QString("DiffusionImage").compare(node->GetData()->GetNameOfClass())==0) + { + diffImage = static_cast*>((node)->GetData()); + } + else if((QString("TensorImage").compare(node->GetData()->GetNameOfClass())==0)) + { + mitk::TensorImage* mitkVol; + mitkVol = static_cast((node)->GetData()); + mitk::CastToItkImage(mitkVol, tensorImage); + node->GetStringProperty("name", nodename); + } + } + } + + + + typedef itk::TensorImageToDiffusionImageFilter< + TTensorPixelType, DiffusionPixelType > FilterType; + + FilterType::GradientListType gradientList; + mitk::DiffusionImage::GradientDirectionContainerType* gradients + = diffImage->GetDirections(); + + // Copy gradients vectors from gradients to gradientList + + + + for(int i=0; iSize(); i++) + { + mitk::DiffusionImage::GradientDirectionType vec = gradients->at(i); + itk::Vector grad; + + grad[0] = vec[0]; + grad[1] = vec[1]; + grad[2] = vec[2]; + + gradientList.push_back(grad); + + + } + + + + //Initialize filter that calculates the modeled diffusion weighted signals + FilterType::Pointer filter = FilterType::New(); + filter->SetInput( tensorImage ); + filter->SetBValue(diffImage->GetB_Value()); + filter->SetGradientList(gradientList); + filter->Update(); + + + // TENSORS TO DATATREE + mitk::DiffusionImage::Pointer image = mitk::DiffusionImage::New(); + image->SetVectorImage( filter->GetOutput() ); + image->SetB_Value(diffImage->GetB_Value()); + image->SetDirections(gradientList); + image->SetOriginalDirections(gradientList); + image->InitializeFromVectorImage(); + mitk::DataNode::Pointer node=mitk::DataNode::New(); + node->SetData( image ); + + + QString newname; + newname = newname.append(nodename.c_str()); + newname = newname.append("_dwi"); + node->SetName(newname.toAscii()); + + + GetDefaultDataStorage()->Add(node); + + + m_MultiWidget->RequestUpdate(); + + + } +} + void QmitkTensorReconstructionView::ItkReconstruction() { Reconstruct(0); } void QmitkTensorReconstructionView::TeemReconstruction() { Reconstruct(1); } void QmitkTensorReconstructionView::Reconstruct(int method) { if (m_CurrentSelection) { mitk::DataStorage::SetOfObjects::Pointer set = mitk::DataStorage::SetOfObjects::New(); int at = 0; for (IStructuredSelection::iterator i = m_CurrentSelection->Begin(); i != m_CurrentSelection->End(); ++i) { if (mitk::DataNodeObject::Pointer nodeObj = i->Cast()) { mitk::DataNode::Pointer node = nodeObj->GetDataNode(); if(QString("DiffusionImage").compare(node->GetData()->GetNameOfClass())==0) { set->InsertElement(at++, node); } } } if(method == 0) { ItkTensorReconstruction(set); } if(method == 1) { TeemTensorReconstruction(set); } } } 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 nodes; while ( itemiter != itemiterend ) // for all items { mitk::DiffusionImage* vols = static_cast*>( (*itemiter)->GetData()); std::string nodename; (*itemiter)->GetStringProperty("name", nodename); ++itemiter; // TENSOR RECONSTRUCTION clock.Start(); MBI_INFO << "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(); tensorReconstructionFilter->SetGradientImage( vols->GetDirections(), vols->GetVectorImage() ); tensorReconstructionFilter->SetBValue(vols->GetB_Value()); tensorReconstructionFilter->SetThreshold( m_Controls->m_TensorReconstructionThreasholdEdit->text().toFloat() ); tensorReconstructionFilter->Update(); clock.Stop(); MBI_DEBUG << "took " << clock.GetMeanTime() << "s."; // TENSORS TO DATATREE mitk::TensorImage::Pointer image = mitk::TensorImage::New(); typedef itk::Image, 3> TensorImageType; TensorImageType::Pointer tensorImage; tensorImage = tensorReconstructionFilter->GetOutput(); // Check the tensor for negative eigenvalues if(m_Controls->m_CheckNegativeEigenvalues->isChecked()) { typedef itk::ImageRegionIterator TensorImageIteratorType; TensorImageIteratorType tensorIt(tensorImage, tensorImage->GetRequestedRegion()); tensorIt.GoToBegin(); while(!tensorIt.IsAtEnd()) { typedef itk::DiffusionTensor3D TensorType; //typedef itk::Tensor TensorType2; TensorType tensor = tensorIt.Get(); // TensorType2 tensor2; /* for(int i=0; i SymEigenSystemType; SymEigenSystemType eig (tensor2.GetVnlMatrix()); for(unsigned int i=0; iInitializeByItk( 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::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) { MBI_INFO << ex ; return ; } } void QmitkTensorReconstructionView::TeemTensorReconstruction (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 nodes; while ( itemiter != itemiterend ) // for all items { mitk::DiffusionImage* vols = static_cast*>( (*itemiter)->GetData()); std::string nodename; (*itemiter)->GetStringProperty("name", nodename); ++itemiter; // TENSOR RECONSTRUCTION clock.Start(); MBI_INFO << "Teem Tensor reconstruction "; mitk::StatusBar::GetInstance()->DisplayText(status.sprintf( "Teem Tensor reconstruction for %s", nodename.c_str()).toAscii()); typedef mitk::TeemDiffusionTensor3DReconstructionImageFilter< DiffusionPixelType, TTensorPixelType > TensorReconstructionImageFilterType; TensorReconstructionImageFilterType::Pointer tensorReconstructionFilter = TensorReconstructionImageFilterType::New(); tensorReconstructionFilter->SetInput( vols ); if(!m_Controls->m_TensorEstimationTeemSigmaEdit->text().contains(QString("NaN"))) tensorReconstructionFilter->SetSigma( m_Controls->m_TensorEstimationTeemSigmaEdit->text().toFloat() ); switch(m_Controls->m_TensorEstimationTeemEstimationMethodCombo->currentIndex()) { // items << "LLS (Linear Least Squares)" //<< "MLE (Maximum Likelihood)" //<< "NLS (Nonlinear Least Squares)" //<< "WLS (Weighted Least Squares)"; case 0: tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsLLS); break; case 1: tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsMLE); break; case 2: tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsNLS); break; case 3: tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsWLS); break; default: tensorReconstructionFilter->SetEstimationMethod(mitk::TeemTensorEstimationMethodsLLS); } tensorReconstructionFilter->SetNumIterations( m_Controls->m_TensorEstimationTeemNumItsSpin->value() ); if(m_Controls->m_TensorEstimationManualThreashold->isChecked()) tensorReconstructionFilter->SetConfidenceThreshold( m_Controls->m_TensorReconstructionThreasholdEdit_2->text().toDouble() ); tensorReconstructionFilter->SetConfidenceFuzzyness( m_Controls->m_TensorEstimationTeemFuzzyEdit->text().toFloat() ); tensorReconstructionFilter->SetMinPlausibleValue( m_Controls->m_TensorEstimationTeemMinValEdit->text().toDouble() ); tensorReconstructionFilter->Update(); clock.Stop(); MBI_DEBUG << "took " << clock.GetMeanTime() << "s." ; // TENSORS TO DATATREE mitk::DataNode::Pointer node2=mitk::DataNode::New(); node2->SetData( tensorReconstructionFilter->GetOutputItk() ); QString newname; newname = newname.append(nodename.c_str()); newname = newname.append("_dtix"); SetDefaultNodeProperties(node2, newname.toStdString()); nodes.push_back(node2); mitk::ProgressBar::GetInstance()->Progress(); } std::vector::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) { MBI_INFO << ex ; return ; } } void QmitkTensorReconstructionView::SetDefaultNodeProperties(mitk::DataNode::Pointer node, std::string name) { node->SetProperty( "ShowMaxNumber", mitk::IntProperty::New( 500 ) ); node->SetProperty( "Scaling", mitk::FloatProperty::New( 1.0 ) ); node->SetProperty( "Normalization", mitk::OdfNormalizationMethodProperty::New()); node->SetProperty( "ScaleBy", mitk::OdfScaleByProperty::New()); node->SetProperty( "IndexParam1", mitk::FloatProperty::New(2)); node->SetProperty( "IndexParam2", mitk::FloatProperty::New(1)); node->SetProperty( "visible", mitk::BoolProperty::New( true ) ); node->SetProperty( "VisibleOdfs", mitk::BoolProperty::New( false ) ); node->SetProperty ("layer", mitk::IntProperty::New(100)); node->SetProperty( "DoRefresh", mitk::BoolProperty::New( true ) ); //node->SetProperty( "opacity", mitk::FloatProperty::New(1.0f) ); node->SetProperty( "name", mitk::StringProperty::New(name) ); } //node->SetProperty( "volumerendering", mitk::BoolProperty::New( false ) ); //node->SetProperty( "use color", mitk::BoolProperty::New( true ) ); //node->SetProperty( "texture interpolation", mitk::BoolProperty::New( true ) ); //node->SetProperty( "reslice interpolation", mitk::VtkResliceInterpolationProperty::New() ); //node->SetProperty( "layer", mitk::IntProperty::New(0)); //node->SetProperty( "in plane resample extent by geometry", mitk::BoolProperty::New( false ) ); //node->SetOpacity(1.0f); //node->SetColor(1.0,1.0,1.0); //node->SetVisibility(true); //node->SetProperty( "IsTensorVolume", mitk::BoolProperty::New( true ) ); //mitk::LevelWindowProperty::Pointer levWinProp = mitk::LevelWindowProperty::New(); //mitk::LevelWindow levelwindow; //// levelwindow.SetAuto( image ); //levWinProp->SetLevelWindow( levelwindow ); //node->GetPropertyList()->SetProperty( "levelwindow", levWinProp ); //// add a default rainbow lookup table for color mapping //if(!node->GetProperty("LookupTable")) //{ // mitk::LookupTable::Pointer mitkLut = mitk::LookupTable::New(); // vtkLookupTable* vtkLut = mitkLut->GetVtkLookupTable(); // vtkLut->SetHueRange(0.6667, 0.0); // vtkLut->SetTableRange(0.0, 20.0); // vtkLut->Build(); // mitk::LookupTableProperty::Pointer mitkLutProp = mitk::LookupTableProperty::New(); // mitkLutProp->SetLookupTable(mitkLut); // node->SetProperty( "LookupTable", mitkLutProp ); //} //if(!node->GetProperty("binary")) // node->SetProperty( "binary", mitk::BoolProperty::New( false ) ); //// add a default transfer function //mitk::TransferFunction::Pointer tf = mitk::TransferFunction::New(); //node->SetProperty ( "TransferFunction", mitk::TransferFunctionProperty::New ( tf.GetPointer() ) ); //// set foldername as string property //mitk::StringProperty::Pointer nameProp = mitk::StringProperty::New( name ); //node->SetProperty( "name", nameProp ); void QmitkTensorReconstructionView::TensorsToDWI() { if (m_CurrentSelection) { mitk::DataStorage::SetOfObjects::Pointer set = mitk::DataStorage::SetOfObjects::New(); int at = 0; for (IStructuredSelection::iterator i = m_CurrentSelection->Begin(); i != m_CurrentSelection->End(); ++i) { if (mitk::DataNodeObject::Pointer nodeObj = i->Cast()) { mitk::DataNode::Pointer node = nodeObj->GetDataNode(); if(QString("TensorImage").compare(node->GetData()->GetNameOfClass())==0) { set->InsertElement(at++, node); } } } DoTensorsToDWI(set); } } void QmitkTensorReconstructionView::TensorsToQbi() { std::vector nodes = this->GetDataManagerSelection(); for (int i=0; i TensorPixelType; typedef itk::Image< TensorPixelType, 3 > TensorImageType; TensorImageType::Pointer itkvol = TensorImageType::New(); mitk::CastToItkImage(dynamic_cast(tensorImageNode->GetData()), itkvol); typedef itk::TensorImageToQBallImageFilter< TTensorPixelType, TTensorPixelType > FilterType; FilterType::Pointer filter = FilterType::New(); filter->SetInput( itkvol ); filter->Update(); typedef itk::Vector OutputPixelType; typedef itk::Image OutputImageType; mitk::QBallImage::Pointer image = mitk::QBallImage::New(); OutputImageType::Pointer outimg = filter->GetOutput(); image->InitializeByItk( outimg.GetPointer() ); image->SetVolume( outimg->GetBufferPointer() ); mitk::DataNode::Pointer node = mitk::DataNode::New(); node->SetData( image ); QString newname; newname = newname.append(tensorImageNode->GetName().c_str()); newname = newname.append("_qbi"); node->SetName(newname.toAscii()); GetDefaultDataStorage()->Add(node); } } void QmitkTensorReconstructionView::OnSelectionChanged( std::vector nodes ) { if ( !this->IsVisible() ) return; } template std::vector > QmitkTensorReconstructionView::MakeGradientList() { std::vector > retval; vnl_matrix_fixed* U = itk::PointShell >::DistributePointShell(); for(int i=0; i v; v[0] = U->get(0,i); v[1] = U->get(1,i); v[2] = U->get(2,i); retval.push_back(v); } return retval; } void QmitkTensorReconstructionView::DoTensorsToDWI (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 nodes; while ( itemiter != itemiterend ) // for all items { std::string nodename; (*itemiter)->GetStringProperty("name", nodename); mitk::TensorImage* vol = static_cast((*itemiter)->GetData()); ++itemiter; typedef float TTensorPixelType; typedef itk::DiffusionTensor3D< TTensorPixelType > TensorPixelType; typedef itk::Image< TensorPixelType, 3 > TensorImageType; TensorImageType::Pointer itkvol = TensorImageType::New(); mitk::CastToItkImage(vol, itkvol); typedef itk::TensorImageToDiffusionImageFilter< TTensorPixelType, DiffusionPixelType > FilterType; FilterType::GradientListType gradientList; switch(m_Controls->m_TensorsToDWINumDirsSelect->currentIndex()) { case 0: gradientList = MakeGradientList<12>(); break; case 1: gradientList = MakeGradientList<42>(); break; case 2: gradientList = MakeGradientList<92>(); break; case 3: gradientList = MakeGradientList<162>(); break; case 4: gradientList = MakeGradientList<252>(); break; case 5: gradientList = MakeGradientList<362>(); break; case 6: gradientList = MakeGradientList<492>(); break; case 7: gradientList = MakeGradientList<642>(); break; case 8: gradientList = MakeGradientList<812>(); break; case 9: gradientList = MakeGradientList<1002>(); break; default: gradientList = MakeGradientList<92>(); } double bVal = m_Controls->m_TensorsToDWIBValueEdit->text().toDouble(); // DWI ESTIMATION clock.Start(); MBI_INFO << "DWI Estimation "; mitk::StatusBar::GetInstance()->DisplayText(status.sprintf( "DWI Estimation for %s", nodename.c_str()).toAscii()); FilterType::Pointer filter = FilterType::New(); filter->SetInput( itkvol ); filter->SetBValue(bVal); filter->SetGradientList(gradientList); //filter->SetNumberOfThreads(1); filter->Update(); clock.Stop(); MBI_DEBUG << "took " << clock.GetMeanTime() << "s."; itk::Vector v; v[0] = 0; v[1] = 0; v[2] = 0; gradientList.push_back(v); // TENSORS TO DATATREE mitk::DiffusionImage::Pointer image = mitk::DiffusionImage::New(); image->SetVectorImage( filter->GetOutput() ); image->SetB_Value(bVal); image->SetDirections(gradientList); image->SetOriginalDirections(gradientList); image->InitializeFromVectorImage(); mitk::DataNode::Pointer node=mitk::DataNode::New(); node->SetData( image ); mitk::DiffusionImageMapper::SetDefaultProperties(node); QString newname; newname = newname.append(nodename.c_str()); newname = newname.append("_dwi"); node->SetName(newname.toAscii()); nodes.push_back(node); mitk::ProgressBar::GetInstance()->Progress(); } std::vector::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) { MBI_INFO << ex ; return ; } } diff --git a/Modules/Bundles/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.h b/Modules/Bundles/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.h index c81ad3f745..4e8996cf88 100644 --- a/Modules/Bundles/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.h +++ b/Modules/Bundles/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkTensorReconstructionView.h @@ -1,123 +1,124 @@ /*========================================================================= Program: Medical Imaging & Interaction Toolkit Module: $RCSfile$ Language: C++ Date: $Date: 2009-05-28 17:19:30 +0200 (Do, 28 Mai 2009) $ Version: $Revision: 17495 $ Copyright (c) German Cancer Research Center, Division of Medical and Biological Informatics. All rights reserved. See MITKCopyright.txt or http://www.mitk.org/copyright.html for details. This software is distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the above copyright notices for more information. =========================================================================*/ #ifndef _QMITKTENSORRECONSTRUCTIONVIEW_H_INCLUDED #define _QMITKTENSORRECONSTRUCTIONVIEW_H_INCLUDED #include #include #include "ui_QmitkTensorReconstructionViewControls.h" #include #include #include #include #include typedef short DiffusionPixelType; struct TrSelListener; /*! * \ingroup org_mitk_gui_qt_tensorreconstruction_internal * * \brief QmitkTensorReconstructionView * * Document your class here. * * \sa QmitkFunctionality */ class QmitkTensorReconstructionView : public QmitkFunctionality { friend struct TrSelListener; // this is needed for all Qt objects that should have a MOC object (everything that derives from QObject) Q_OBJECT public: static const std::string VIEW_ID; QmitkTensorReconstructionView(); QmitkTensorReconstructionView(const QmitkTensorReconstructionView& other); virtual ~QmitkTensorReconstructionView(); virtual void CreateQtPartControl(QWidget *parent); /// \brief Creation of the connections of main and control widget virtual void CreateConnections(); /// \brief Called when the functionality is activated virtual void Activated(); virtual void Deactivated(); virtual void StdMultiWidgetAvailable (QmitkStdMultiWidget &stdMultiWidget); virtual void StdMultiWidgetNotAvailable(); static const int nrconvkernels; protected slots: void TensorsToQbi(); void TensorsToDWI(); void DoTensorsToDWI(mitk::DataStorage::SetOfObjects::Pointer inImages); void TeemCheckboxClicked(); void Advanced1CheckboxClicked(); void Advanced2CheckboxClicked(); void ManualThresholdClicked(); void MethodChoosen(int method); void Reconstruct(int method); void TeemReconstruction(); void ItkReconstruction(); + void ResidualCalculation(); protected: void ItkTensorReconstruction (mitk::DataStorage::SetOfObjects::Pointer inImages); void TeemTensorReconstruction (mitk::DataStorage::SetOfObjects::Pointer inImages); void OnSelectionChanged( std::vector nodes ); Ui::QmitkTensorReconstructionViewControls* m_Controls; QmitkStdMultiWidget* m_MultiWidget; template std::vector > MakeGradientList() ; template void TemplatedAnalyticalTensorReconstruction(mitk::DiffusionImage* vols, float lambda, std::string nodename, std::vector* nodes, int normalization); void SetDefaultNodeProperties(mitk::DataNode::Pointer node, std::string name); berry::ISelectionListener::Pointer m_SelListener; berry::IStructuredSelection::ConstPointer m_CurrentSelection; }; #endif // _QMITKTENSORRECONSTRUCTIONVIEW_H_INCLUDED