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());
}
}