void QmitkPreprocessingView::DoAdcCalculation()
{
if (m_DiffusionImage.IsNull())
return;
typedef mitk::DiffusionImage< DiffusionPixelType > DiffusionImageType;
typedef itk::AdcImageFilter< DiffusionPixelType, double > FilterType;
for (unsigned int i=0; i<m_SelectedDiffusionNodes.size(); i++)
{
DiffusionImageType::Pointer inImage = dynamic_cast< DiffusionImageType* >(m_SelectedDiffusionNodes.at(i)->GetData());
FilterType::Pointer filter = FilterType::New();
filter->SetInput(inImage->GetVectorImage());
filter->SetGradientDirections(inImage->GetDirections());
filter->SetB_value(inImage->GetReferenceBValue());
filter->Update();
mitk::Image::Pointer image = mitk::Image::New();
image->InitializeByItk( filter->GetOutput() );
image->SetVolume( filter->GetOutput()->GetBufferPointer() );
mitk::DataNode::Pointer imageNode = mitk::DataNode::New();
imageNode->SetData( image );
QString name = m_SelectedDiffusionNodes.at(i)->GetName().c_str();
imageNode->SetName((name+"_ADC").toStdString().c_str());
GetDefaultDataStorage()->Add(imageNode);
}
}
/**
* Denoises DWI using the Nonlocal - Means algorithm
*/
int DwiDenoising(int argc, char* argv[])
{
ctkCommandLineParser parser;
parser.setArgumentPrefix("--", "-");
parser.addArgument("input", "i", ctkCommandLineParser::String, "input image (DWI)", us::Any(), false);
parser.addArgument("variance", "v", ctkCommandLineParser::Float, "noise variance", us::Any(), false);
parser.addArgument("mask", "m", ctkCommandLineParser::String, "brainmask for input image", us::Any(), true);
parser.addArgument("search", "s", ctkCommandLineParser::Int, "search radius", us::Any(), true);
parser.addArgument("compare", "c", ctkCommandLineParser::Int, "compare radius", us::Any(), true);
parser.addArgument("joint", "j", ctkCommandLineParser::Bool, "use joint information");
parser.addArgument("rician", "r", ctkCommandLineParser::Bool, "use rician adaption");
map<string, us::Any> parsedArgs = parser.parseArguments(argc, argv);
if (parsedArgs.size()==0)
return EXIT_FAILURE;
string inFileName = us::any_cast<string>(parsedArgs["input"]);
double variance = static_cast<double>(us::any_cast<float>(parsedArgs["variance"]));
string maskName;
if (parsedArgs.count("mask"))
maskName = us::any_cast<string>(parsedArgs["mask"]);
string outFileName = inFileName;
boost::algorithm::erase_all(outFileName, ".dwi");
int search = 4;
if (parsedArgs.count("search"))
search = us::any_cast<int>(parsedArgs["search"]);
int compare = 1;
if (parsedArgs.count("compare"))
compare = us::any_cast<int>(parsedArgs["compare"]);
bool joint = false;
if (parsedArgs.count("joint"))
joint = true;
bool rician = false;
if (parsedArgs.count("rician"))
rician = true;
try
{
if( boost::algorithm::ends_with(inFileName, ".dwi"))
{
DiffusionImageType::Pointer dwi = dynamic_cast<DiffusionImageType*>(LoadFile(inFileName).GetPointer());
itk::NonLocalMeansDenoisingFilter<short>::Pointer filter = itk::NonLocalMeansDenoisingFilter<short>::New();
filter->SetNumberOfThreads(12);
filter->SetInputImage(dwi->GetVectorImage());
if (!maskName.empty())
{
mitk::Image::Pointer mask = dynamic_cast<mitk::Image*>(LoadFile(maskName).GetPointer());
ImageType::Pointer itkMask = ImageType::New();
mitk::CastToItkImage(mask, itkMask);
filter->SetInputMask(itkMask);
}
filter->SetUseJointInformation(joint);
filter->SetUseRicianAdaption(rician);
filter->SetSearchRadius(search);
filter->SetComparisonRadius(compare);
filter->SetVariance(variance);
filter->Update();
DiffusionImageType::Pointer output = DiffusionImageType::New();
output->SetVectorImage(filter->GetOutput());
output->SetReferenceBValue(dwi->GetReferenceBValue());
output->SetDirections(dwi->GetDirections());
output->InitializeFromVectorImage();
std::stringstream name;
name << outFileName << "_NLM_" << search << "-" << compare << "-" << variance << ".dwi";
MITK_INFO << "Writing: " << name.str();
mitk::NrrdDiffusionImageWriter<short>::Pointer writer = mitk::NrrdDiffusionImageWriter<short>::New();
writer->SetInput(output);
writer->SetFileName(name.str());
writer->Update();
MITK_INFO << "Finish!";
}
else
{
MITK_INFO << "Only supported for .dwi!";
}
}
catch (itk::ExceptionObject e)
{
MITK_INFO << e;
return EXIT_FAILURE;
}
catch (std::exception e)
{
MITK_INFO << e.what();
return EXIT_FAILURE;
}
catch (...)
{
MITK_INFO << "ERROR!?!";
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
void mitk::RegistrationWrapper::ApplyTransformationToImage(mitk::Image::Pointer img, const mitk::RegistrationWrapper::RidgidTransformType &transformation,double* offset, mitk::Image* resampleReference, bool binary)
{
typedef mitk::DiffusionImage<short> DiffusionImageType;
if (dynamic_cast<DiffusionImageType*> (img.GetPointer()) == NULL)
{
ItkImageType::Pointer itkImage = ItkImageType::New();
MITK_ERROR << "imgCopy 0 " << "/" << img->GetReferenceCount();
MITK_ERROR << "pixel type " << img->GetPixelType().GetComponentTypeAsString();
CastToItkImage(img, itkImage);
typedef itk::Euler3DTransform< double > RigidTransformType;
RigidTransformType::Pointer rtransform = RigidTransformType::New();
RigidTransformType::ParametersType parameters(RigidTransformType::ParametersDimension);
for (int i = 0; i<6;++i)
parameters[i] = transformation[i];
rtransform->SetParameters( parameters );
mitk::Point3D origin = itkImage->GetOrigin();
origin[0]-=offset[0];
origin[1]-=offset[1];
origin[2]-=offset[2];
mitk::Point3D newOrigin = rtransform->GetInverseTransform()->TransformPoint(origin);
itk::Matrix<double,3,3> dir = itkImage->GetDirection();
itk::Matrix<double,3,3> transM ( vnl_inverse(rtransform->GetMatrix().GetVnlMatrix()));
itk::Matrix<double,3,3> newDirection = transM * dir;
itkImage->SetOrigin(newOrigin);
itkImage->SetDirection(newDirection);
// Perform Resampling if reference image is provided
if (resampleReference != NULL)
{
typedef itk::ResampleImageFilter<ItkImageType, ItkImageType> ResampleFilterType;
ItkImageType::Pointer itkReference = ItkImageType::New();
CastToItkImage(resampleReference,itkReference);
typedef itk::WindowedSincInterpolateImageFunction< ItkImageType, 3> WindowedSincInterpolatorType;
WindowedSincInterpolatorType::Pointer sinc_interpolator = WindowedSincInterpolatorType::New();
typedef itk::NearestNeighborInterpolateImageFunction< ItkImageType, double > NearestNeighborInterpolatorType;
NearestNeighborInterpolatorType::Pointer nn_interpolator = NearestNeighborInterpolatorType::New();
ResampleFilterType::Pointer resampler = ResampleFilterType::New();
resampler->SetInput(itkImage);
resampler->SetReferenceImage( itkReference );
resampler->UseReferenceImageOn();
if (binary)
resampler->SetInterpolator(nn_interpolator);
else
resampler->SetInterpolator(sinc_interpolator);
resampler->Update();
GrabItkImageMemory(resampler->GetOutput(), img);
}
else
{
// !! CastToItk behaves very differently depending on the original data type
// if the target type is the same as the original, only a pointer to the data is set
// and an additional GrabItkImageMemory will cause a segfault when the image is destroyed
// GrabItkImageMemory - is not necessary in this case since we worked on the original data
// See Bug 17538.
if (img->GetPixelType().GetComponentTypeAsString() != "double")
img = GrabItkImageMemory(itkImage);
}
}
else
{
DiffusionImageType::Pointer diffImages = dynamic_cast<DiffusionImageType*>(img.GetPointer());
typedef itk::Euler3DTransform< double > RigidTransformType;
RigidTransformType::Pointer rtransform = RigidTransformType::New();
RigidTransformType::ParametersType parameters(RigidTransformType::ParametersDimension);
for (int i = 0; i<6;++i)
{
parameters[i] = transformation[i];
}
rtransform->SetParameters( parameters );
mitk::Point3D b0origin = diffImages->GetVectorImage()->GetOrigin();
b0origin[0]-=offset[0];
b0origin[1]-=offset[1];
b0origin[2]-=offset[2];
mitk::Point3D newOrigin = rtransform->GetInverseTransform()->TransformPoint(b0origin);
itk::Matrix<double,3,3> dir = diffImages->GetVectorImage()->GetDirection();
itk::Matrix<double,3,3> transM ( vnl_inverse(rtransform->GetMatrix().GetVnlMatrix()));
itk::Matrix<double,3,3> newDirection = transM * dir;
diffImages->GetVectorImage()->SetOrigin(newOrigin);
diffImages->GetVectorImage()->SetDirection(newDirection);
diffImages->Modified();
mitk::DiffusionImageCorrectionFilter<short>::Pointer correctionFilter = mitk::DiffusionImageCorrectionFilter<short>::New();
// For Diff. Images: Need to rotate the gradients (works in-place)
correctionFilter->SetImage(diffImages);
correctionFilter->CorrectDirections(transM.GetVnlMatrix());
img = diffImages;
}
}