void QmitkPreprocessingView::CallMultishellToSingleShellFilter(itk::DWIVoxelFunctor * functor, mitk::DiffusionImage<DiffusionPixelType>::Pointer ImPtr, QString imageName)
{
typedef itk::RadialMultishellToSingleshellImageFilter<DiffusionPixelType, DiffusionPixelType> FilterType;
// filter input parameter
const mitk::DiffusionImage<DiffusionPixelType>::BValueMap
&originalShellMap = ImPtr->GetBValueMap();
const mitk::DiffusionImage<DiffusionPixelType>::ImageType
*vectorImage = ImPtr->GetVectorImage();
const mitk::DiffusionImage<DiffusionPixelType>::GradientDirectionContainerType::Pointer
gradientContainer = ImPtr->GetDirections();
const unsigned int
&bValue = ImPtr->GetReferenceBValue();
mitk::DataNode::Pointer imageNode = 0;
// filter call
FilterType::Pointer filter = FilterType::New();
filter->SetInput(vectorImage);
filter->SetOriginalGradientDirections(gradientContainer);
filter->SetOriginalBValueMap(originalShellMap);
filter->SetOriginalBValue(bValue);
filter->SetFunctor(functor);
filter->Update();
// create new DWI image
mitk::DiffusionImage<DiffusionPixelType>::Pointer outImage = mitk::DiffusionImage<DiffusionPixelType>::New();
outImage->SetVectorImage( filter->GetOutput() );
outImage->SetReferenceBValue( m_Controls->m_targetBValueSpinBox->value() );
outImage->SetDirections( filter->GetTargetGradientDirections() );
outImage->InitializeFromVectorImage();
imageNode = mitk::DataNode::New();
imageNode->SetData( outImage );
imageNode->SetName(imageName.toStdString().c_str());
GetDefaultDataStorage()->Add(imageNode);
if(m_Controls->m_OutputRMSErrorImage->isChecked()){
// create new Error image
FilterType::ErrorImageType::Pointer errImage = filter->GetErrorImage();
mitk::Image::Pointer mitkErrImage = mitk::Image::New();
mitkErrImage->InitializeByItk<FilterType::ErrorImageType>(errImage);
mitkErrImage->SetVolume(errImage->GetBufferPointer());
imageNode = mitk::DataNode::New();
imageNode->SetData( mitkErrImage );
imageNode->SetName((imageName+"_Error").toStdString().c_str());
GetDefaultDataStorage()->Add(imageNode);
}
}
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);
}
}
void QmitkPreprocessingView::DoLengthCorrection()
{
if (m_DiffusionImage.IsNull())
return;
typedef mitk::DiffusionImage<DiffusionPixelType> DiffusionImageType;
typedef itk::DwiGradientLengthCorrectionFilter FilterType;
FilterType::Pointer filter = FilterType::New();
filter->SetRoundingValue( m_Controls->m_B_ValueMap_Rounder_SpinBox->value());
filter->SetReferenceBValue(m_DiffusionImage->GetReferenceBValue());
filter->SetReferenceGradientDirectionContainer(m_DiffusionImage->GetDirections());
filter->Update();
DiffusionImageType::Pointer image = DiffusionImageType::New();
image->SetVectorImage( m_DiffusionImage->GetVectorImage());
image->SetReferenceBValue( filter->GetNewBValue() );
image->SetDirections( filter->GetOutputGradientDirectionContainer());
image->InitializeFromVectorImage();
mitk::DataNode::Pointer imageNode = mitk::DataNode::New();
imageNode->SetData( image );
QString name = m_SelectedDiffusionNodes.front()->GetName().c_str();
imageNode->SetName((name+"_rounded").toStdString().c_str());
GetDefaultDataStorage()->Add(imageNode);
}
void QmitkDenoisingView::AfterThread()
{
m_ThreadIsRunning = false;
// stop timer to stop updates of progressbar
m_DenoisingTimer->stop();
// make sure progressbar is finished
mitk::ProgressBar::GetInstance()->Progress(m_MaxProgressCount);
if (m_CompletedCalculation)
{
switch (m_SelectedFilter)
{
case NOFILTERSELECTED:
case GAUSS:
{
break;
}
case NLM:
{
DiffusionImageType::Pointer image = DiffusionImageType::New();
image->SetVectorImage(m_NonLocalMeansFilter->GetOutput());
image->SetReferenceBValue(m_InputImage->GetReferenceBValue());
image->SetDirections(m_InputImage->GetDirections());
image->InitializeFromVectorImage();
mitk::DataNode::Pointer imageNode = mitk::DataNode::New();
imageNode->SetData( image );
QString name = m_ImageNode->GetName().c_str();
//TODO: Rician adaption & joint information in name
if (m_Controls->m_RicianCheckbox->isChecked() && !m_Controls->m_JointInformationCheckbox->isChecked())
{
imageNode->SetName((name+"_NLMr_"+QString::number(m_Controls->m_SpinBoxParameter1->value())+"-"+QString::number(m_Controls->m_SpinBoxParameter2->value())).toStdString().c_str());
}
else if(!m_Controls->m_RicianCheckbox->isChecked() && m_Controls->m_JointInformationCheckbox->isChecked())
{
imageNode->SetName((name+"_NLMv_"+QString::number(m_Controls->m_SpinBoxParameter1->value())+"-"+QString::number(m_Controls->m_SpinBoxParameter2->value())).toStdString().c_str());
}
else if(m_Controls->m_RicianCheckbox->isChecked() && m_Controls->m_JointInformationCheckbox->isChecked())
{
imageNode->SetName((name+"_NLMvr_"+QString::number(m_Controls->m_SpinBoxParameter1->value())+"-"+QString::number(m_Controls->m_SpinBoxParameter2->value())).toStdString().c_str());
}
else
{
imageNode->SetName((name+"_NLM_"+QString::number(m_Controls->m_SpinBoxParameter1->value())+"-"+QString::number(m_Controls->m_SpinBoxParameter2->value())).toStdString().c_str());
}
GetDefaultDataStorage()->Add(imageNode);
break;
}
}
}
m_Controls->m_ParameterBox->setEnabled(true);
m_Controls->m_ApplyButton->setText("Apply");
}
void QmitkDiffusionQuantificationView::TensorQuantification(
mitk::DataStorage::SetOfObjects::Pointer inImages, int method)
{
itk::TimeProbe clock;
QString status;
int nrFiles = inImages->size();
if (!nrFiles) return;
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 float TTensorPixelType;
typedef itk::DiffusionTensor3D< TTensorPixelType > TensorPixelType;
typedef itk::Image< TensorPixelType, 3 > TensorImageType;
mitk::Image* vol =
static_cast<mitk::Image*>((*itemiter)->GetData());
TensorImageType::Pointer itkvol = TensorImageType::New();
mitk::CastToItkImage<TensorImageType>(vol, itkvol);
std::string nodename;
(*itemiter)->GetStringProperty("name", nodename);
++itemiter;
// COMPUTE FA
clock.Start();
MBI_INFO << "Computing FA ";
mitk::StatusBar::GetInstance()->DisplayText(status.sprintf(
"Computing FA for %s", nodename.c_str()).toAscii());
typedef itk::Image< TTensorPixelType, 3 > FAImageType;
typedef itk::ShiftScaleImageFilter<FAImageType, FAImageType>
ShiftScaleFilterType;
ShiftScaleFilterType::Pointer multi =
ShiftScaleFilterType::New();
multi->SetShift(0.0);
multi->SetScale(m_Controls->m_ScaleImageValuesBox->value());//itk::NumericTraits<RealValueType>::max()
typedef itk::TensorDerivedMeasurementsFilter<TTensorPixelType> MeasurementsType;
if(method == 0) //FA
{
/* typedef itk::TensorFractionalAnisotropyImageFilter<
TensorImageType, FAImageType > FilterType;
FilterType::Pointer anisotropyFilter = FilterType::New();
anisotropyFilter->SetInput( itkvol.GetPointer() );
anisotropyFilter->Update();
multi->SetInput(anisotropyFilter->GetOutput());
nodename = QString(nodename.c_str()).append("_FA").toStdString();*/
MeasurementsType::Pointer measurementsCalculator = MeasurementsType::New();
measurementsCalculator->SetInput(itkvol.GetPointer() );
measurementsCalculator->SetMeasure(MeasurementsType::FA);
measurementsCalculator->Update();
multi->SetInput(measurementsCalculator->GetOutput());
nodename = QString(nodename.c_str()).append("_FA").toStdString();
}
else if(method == 1) //RA
{
/*typedef itk::TensorRelativeAnisotropyImageFilter<
TensorImageType, FAImageType > FilterType;
FilterType::Pointer anisotropyFilter = FilterType::New();
anisotropyFilter->SetInput( itkvol.GetPointer() );
anisotropyFilter->Update();
multi->SetInput(anisotropyFilter->GetOutput());
nodename = QString(nodename.c_str()).append("_RA").toStdString();*/
MeasurementsType::Pointer measurementsCalculator = MeasurementsType::New();
measurementsCalculator->SetInput(itkvol.GetPointer() );
measurementsCalculator->SetMeasure(MeasurementsType::RA);
measurementsCalculator->Update();
multi->SetInput(measurementsCalculator->GetOutput());
nodename = QString(nodename.c_str()).append("_RA").toStdString();
}
else if(method == 2) // AD (Axial diffusivity)
{
MeasurementsType::Pointer measurementsCalculator = MeasurementsType::New();
measurementsCalculator->SetInput(itkvol.GetPointer() );
measurementsCalculator->SetMeasure(MeasurementsType::AD);
measurementsCalculator->Update();
multi->SetInput(measurementsCalculator->GetOutput());
nodename = QString(nodename.c_str()).append("_AD").toStdString();
}
else if(method == 3) // RD (Radial diffusivity, (Lambda2+Lambda3)/2
{
MeasurementsType::Pointer measurementsCalculator = MeasurementsType::New();
measurementsCalculator->SetInput(itkvol.GetPointer() );
measurementsCalculator->SetMeasure(MeasurementsType::RD);
measurementsCalculator->Update();
multi->SetInput(measurementsCalculator->GetOutput());
nodename = QString(nodename.c_str()).append("_RD").toStdString();
}
else if(method == 4) // 1-(Lambda2+Lambda3)/(2*Lambda1)
{
MeasurementsType::Pointer measurementsCalculator = MeasurementsType::New();
measurementsCalculator->SetInput(itkvol.GetPointer() );
measurementsCalculator->SetMeasure(MeasurementsType::CA);
measurementsCalculator->Update();
multi->SetInput(measurementsCalculator->GetOutput());
nodename = QString(nodename.c_str()).append("_CA").toStdString();
}
else if(method == 5) // MD (Mean Diffusivity, (Lambda1+Lambda2+Lambda3)/3 )
{
MeasurementsType::Pointer measurementsCalculator = MeasurementsType::New();
measurementsCalculator->SetInput(itkvol.GetPointer() );
measurementsCalculator->SetMeasure(MeasurementsType::MD);
measurementsCalculator->Update();
multi->SetInput(measurementsCalculator->GetOutput());
nodename = QString(nodename.c_str()).append("_MD").toStdString();
}
multi->Update();
clock.Stop();
MBI_DEBUG << "took " << clock.GetMeanTime() << "s.";
// FA TO DATATREE
mitk::Image::Pointer image = mitk::Image::New();
image->InitializeByItk( multi->GetOutput() );
image->SetVolume( multi->GetOutput()->GetBufferPointer() );
mitk::DataNode::Pointer node=mitk::DataNode::New();
node->SetData( image );
node->SetProperty( "name", mitk::StringProperty::New(nodename) );
nodes.push_back(node);
mitk::StatusBar::GetInstance()->DisplayText("Computation complete.");
}
std::vector<mitk::DataNode::Pointer>::iterator nodeIt;
for(nodeIt = nodes.begin(); nodeIt != nodes.end(); ++nodeIt)
GetDefaultDataStorage()->Add(*nodeIt);
m_MultiWidget->RequestUpdate();
}
void QmitkDiffusionQuantificationView::QBIQuantification(
mitk::DataStorage::SetOfObjects::Pointer inImages, int method)
{
itk::TimeProbe clock;
QString status;
int nrFiles = inImages->size();
if (!nrFiles) return;
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 float TOdfPixelType;
const int odfsize = QBALL_ODFSIZE;
typedef itk::Vector<TOdfPixelType,odfsize> OdfVectorType;
typedef itk::Image<OdfVectorType,3> OdfVectorImgType;
mitk::Image* vol =
static_cast<mitk::Image*>((*itemiter)->GetData());
OdfVectorImgType::Pointer itkvol = OdfVectorImgType::New();
mitk::CastToItkImage<OdfVectorImgType>(vol, itkvol);
std::string nodename;
(*itemiter)->GetStringProperty("name", nodename);
++itemiter;
float p1 = m_Controls->m_ParamKEdit->text().toFloat();
float p2 = m_Controls->m_ParamPEdit->text().toFloat();
// COMPUTE RA
clock.Start();
MBI_INFO << "Computing GFA ";
mitk::StatusBar::GetInstance()->DisplayText(status.sprintf(
"Computing GFA for %s", nodename.c_str()).toAscii());
typedef OdfVectorType::ValueType RealValueType;
typedef itk::Image< RealValueType, 3 > RAImageType;
typedef itk::DiffusionQballGeneralizedFaImageFilter<TOdfPixelType,TOdfPixelType,odfsize>
GfaFilterType;
GfaFilterType::Pointer gfaFilter = GfaFilterType::New();
gfaFilter->SetInput(itkvol);
double scale = 1;
std::string newname;
newname.append(nodename);
switch(method)
{
case 0:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_STANDARD);
newname.append("GFA");
break;
}
case 1:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_QUANTILES_HIGH_LOW);
newname.append("01");
break;
}
case 2:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_QUANTILE_HIGH);
newname.append("02");
break;
}
case 3:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_MAX_ODF_VALUE);
newname.append("03");
break;
}
case 4:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_DECONVOLUTION_COEFFS);
newname.append("04");
break;
}
case 5:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_MIN_MAX_NORMALIZED_STANDARD);
newname.append("05");
break;
}
case 6:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_NORMALIZED_ENTROPY);
newname.append("06");
break;
}
case 7:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_NEMATIC_ORDER_PARAMETER);
newname.append("07");
break;
}
case 8:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_QUANTILES_LOW_HIGH);
newname.append("08");
break;
}
case 9:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_QUANTILE_LOW);
newname.append("09");
break;
}
case 10:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_MIN_ODF_VALUE);
newname.append("10");
break;
}
case 11:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_STD_BY_MAX);
newname.append("11");
break;
}
case 12:
{
p1 = m_Controls->MinAngle->text().toFloat();
p2 = m_Controls->MaxAngle->text().toFloat();
gfaFilter->SetComputationMethod(GfaFilterType::GFA_PRINCIPLE_CURVATURE);
QString paramString;
paramString = paramString.append("PC%1-%2").arg(p1).arg(p2);
newname.append(paramString.toAscii());
gfaFilter->SetParam1(p1);
gfaFilter->SetParam2(p2);
break;
}
case 13:
{
gfaFilter->SetComputationMethod(GfaFilterType::GFA_GENERALIZED_GFA);
QString paramString;
paramString = paramString.append("GFAK%1P%2").arg(p1).arg(p2);
newname.append(paramString.toAscii());
gfaFilter->SetParam1(p1);
gfaFilter->SetParam2(p2);
break;
}
default:
{
newname.append("0");
gfaFilter->SetComputationMethod(GfaFilterType::GFA_STANDARD);
}
}
gfaFilter->Update();
clock.Stop();
MBI_DEBUG << "took " << clock.GetMeanTime() << "s.";
typedef itk::Image<TOdfPixelType, 3> ImgType;
ImgType::Pointer img = ImgType::New();
img->SetSpacing( gfaFilter->GetOutput()->GetSpacing() ); // Set the image spacing
img->SetOrigin( gfaFilter->GetOutput()->GetOrigin() ); // Set the image origin
img->SetDirection( gfaFilter->GetOutput()->GetDirection() ); // Set the image direction
img->SetLargestPossibleRegion( gfaFilter->GetOutput()->GetLargestPossibleRegion());
img->SetBufferedRegion( gfaFilter->GetOutput()->GetLargestPossibleRegion() );
img->Allocate();
itk::ImageRegionIterator<ImgType> ot (img, img->GetLargestPossibleRegion() );
ot = ot.Begin();
itk::ImageRegionConstIterator<GfaFilterType::OutputImageType> it
(gfaFilter->GetOutput(), gfaFilter->GetOutput()->GetLargestPossibleRegion() );
it = it.Begin();
for (it = it.Begin(); !it.IsAtEnd(); ++it)
{
GfaFilterType::OutputImageType::PixelType val = it.Get();
ot.Set(val * m_Controls->m_ScaleImageValuesBox->value());
++ot;
}
// GFA TO DATATREE
mitk::Image::Pointer image = mitk::Image::New();
image->InitializeByItk( img.GetPointer() );
image->SetVolume( img->GetBufferPointer() );
mitk::DataNode::Pointer node=mitk::DataNode::New();
node->SetData( image );
node->SetProperty( "name", mitk::StringProperty::New(newname) );
nodes.push_back(node);
mitk::StatusBar::GetInstance()->DisplayText("Computation complete.");
}
std::vector<mitk::DataNode::Pointer>::iterator nodeIt;
for(nodeIt = nodes.begin(); nodeIt != nodes.end(); ++nodeIt)
GetDefaultDataStorage()->Add(*nodeIt);
m_MultiWidget->RequestUpdate();
}
void QmitkDiffusionDicomImport::DicomLoadStartLoad()
{
itk::TimeProbesCollectorBase clock;
bool imageSuccessfullySaved = true;
try
{
const std::string& locale = "C";
const std::string& currLocale = setlocale( LC_ALL, NULL );
if ( locale.compare(currLocale)!=0 )
{
try
{
MITK_INFO << " ** Changing locale from " << setlocale(LC_ALL, NULL) << " to '" << locale << "'";
setlocale(LC_ALL, locale.c_str());
}
catch(...)
{
MITK_INFO << "Could not set locale " << locale;
}
}
int nrFolders = m_Controls->listWidget->count();
if(!nrFolders)
{
Error(QString("No input folders were selected. ABORTING."));
return;
}
Status(QString("GDCM %1 used for DICOM parsing and sorting!").arg(gdcm::Version::GetVersion()));
PrintMemoryUsage();
QString status;
mitk::DataNode::Pointer node;
mitk::ProgressBar::GetInstance()->AddStepsToDo(2*nrFolders);
std::string folder = m_Controls->m_OutputLabel->text().toStdString();
if(berry::Platform::IsWindows())
{
folder.append("\\import.log");
}
else
{
folder.append("/import.log");
}
ofstream logfile;
if(m_OutputFolderNameSet) logfile.open(folder.c_str());
while(m_Controls->listWidget->count())
{
// RETREIVE FOLDERNAME
QListWidgetItem * item = m_Controls->listWidget->takeItem(0);
QString folderName = item->text();
if(m_OutputFolderNameSet) logfile << "Reading " << folderName.toStdString() << '\n';
// PARSING DIRECTORY
PrintMemoryUsage();
clock.Start(folderName.toAscii());
std::vector<std::string> seriesUIDs(0);
std::vector<std::vector<std::string> > seriesFilenames(0);
Status("== Initial Directory Scan ==");
if(m_OutputFolderNameSet) logfile << "== Initial Directory Scan ==\n";
gdcm::Directory d;
d.Load( folderName.toStdString().c_str(), true ); // recursive !
const gdcm::Directory::FilenamesType &l1 = d.GetFilenames();
const unsigned int ntotalfiles = l1.size();
Status(QString(" ... found %1 different files").arg(ntotalfiles));
if(m_OutputFolderNameSet)logfile << "...found " << ntotalfiles << " different files\n";
Status("Scanning Headers");
if(m_OutputFolderNameSet) logfile << "Scanning Headers\n";
gdcm::Scanner s;
const gdcm::Tag t1(0x0020,0x000d); // Study Instance UID
const gdcm::Tag t2(0x0020,0x000e); // Series Instance UID
const gdcm::Tag t5(0x0028, 0x0010); // number rows
const gdcm::Tag t6(0x0028, 0x0011); // number cols
s.AddTag( t1 );
s.AddTag( t2 );
s.AddTag( t5 );
s.AddTag( t6 );
bool b = s.Scan( d.GetFilenames() );
if( !b )
{
Error("Scanner failed");
if(m_OutputFolderNameSet )logfile << "ERROR: scanner failed\n";
continue;
}
// Only get the DICOM files:
gdcm::Directory::FilenamesType l2 = s.GetKeys();
gdcm::Directory::FilenamesType::iterator it;
for (it = l2.begin() ; it != l2.end(); ++it) {
MITK_INFO << "-------FN " << *it;
}
const int nfiles = l2.size();
if(nfiles < 1)
{
Error("No DICOM files found");
if(m_OutputFolderNameSet)logfile << "ERROR: No DICOM files found\n";
continue;
}
Status(QString(" ... successfully scanned %1 headers.").arg(nfiles));
if(m_OutputFolderNameSet) logfile << "...succesfully scanned " << nfiles << " headers\n";
Status("Sorting");
if(m_OutputFolderNameSet) logfile << "Sorting\n";
const gdcm::Scanner::ValuesType &values1 = s.GetValues(t1);
int nvalues;
if(m_Controls->m_DuplicateID->isChecked())
{
nvalues = 1;
}
else
{
nvalues = values1.size();
}
if(nvalues>1)
{
Error("Multiple sSeries tudies found. Please limit to 1 study per folder");
if(m_OutputFolderNameSet) logfile << "Multiple series found. Limit to one. If you are convinced this is an error use the merge duplicate study IDs option \n";
continue;
}
const gdcm::Scanner::ValuesType &values5 = s.GetValues(t5);
const gdcm::Scanner::ValuesType &values6 = s.GetValues(t6);
if(values5.size()>1 || values6.size()>1)
{
Error("Folder contains images of unequal dimensions that cannot be combined in one 3d volume. ABORTING.");
if(m_OutputFolderNameSet) logfile << "Folder contains images of unequal dimensions that cannot be combined in one 3d volume. ABORTING\n.";
continue;
}
const gdcm::Scanner::ValuesType &values2 = s.GetValues(t2);
int nSeries;
if(m_Controls->m_DuplicateID->isChecked())
{
nSeries = 1;
}
else
{
nSeries = values2.size();
}
gdcm::Directory::FilenamesType files;
if(nSeries > 1)
{
gdcm::Sorter sorter;
sorter.SetSortFunction( SortBySeriesUID );
if (sorter.StableSort( l2 ))
{
files = sorter.GetFilenames();
}
else
{
Error("Loading of at least one DICOM file not successfull!");
return;
}
}
else
{
files = l2;
}
unsigned int nTotalAcquis = 0;
if(nfiles % nSeries != 0)
{
Error("Number of files in series not equal, ABORTING");
if(m_OutputFolderNameSet) logfile << "Number of files in series not equal, Some volumes are probably incomplete. ABORTING \n";
continue;
}
int filesPerSeries = nfiles / nSeries;
gdcm::Scanner::ValuesType::const_iterator it2 = values2.begin();
for(int i=0; i<nSeries; i++)
{
gdcm::Directory::FilenamesType sub( files.begin() + i*filesPerSeries, files.begin() + (i+1)*filesPerSeries);
gdcm::Scanner s;
const gdcm::Tag t3(0x0020,0x0012); // Acquisition ID
const gdcm::Tag t4(0x0018,0x0024); // Sequence Name (in case acquisitions are equal for all)
// const gdcm::Tag t5(0x20,0x32) ); // Image Position (Patient)
s.AddTag(t3);
s.AddTag(t4);
// s.AddTag(t5);
bool b = s.Scan( sub );
if( !b )
{
Error("Scanner failed");
if(m_OutputFolderNameSet) logfile << "Scanner failed\n";
continue;
}
gdcm::Sorter subsorter;
gdcm::Scanner::ValuesType::const_iterator it;
const gdcm::Scanner::ValuesType &values3 = s.GetValues(t3);
const gdcm::Scanner::ValuesType &values4 = s.GetValues(t4);;
unsigned int nAcquis = values3.size();
if(nAcquis > 1) // More than one element must have this tag (Not != )
{
subsorter.SetSortFunction( SortByAcquisitionNumber );
it = values3.begin();
}
else if (values4.size() > 1)
{
nAcquis = values4.size();
subsorter.SetSortFunction( SortBySeqName );
it = values4.begin();
}
// Hotfix for Bug 14758, better fix by selecting always availible tags.
else
{
Error("Sorting tags (0x0020,0x0012) and (0x0018,0x0024) missing, ABORTING");
if(m_OutputFolderNameSet) logfile << "Sorting tags (0x0020,0x0012) and (0x0018,0x0024) missing, ABORTING\n";
continue;
}
nTotalAcquis += nAcquis;
subsorter.Sort( sub );
if(filesPerSeries % nAcquis != 0)
{
Error("Number of files per acquisition not equal, ABORTING");
if(m_OutputFolderNameSet) logfile << "Number of files per acquisition not equal, ABORTING \n";
continue;
}
int filesPerAcqu = filesPerSeries / nAcquis;
gdcm::Directory::FilenamesType subfiles = subsorter.GetFilenames();
for ( unsigned int j = 0 ; j < nAcquis ; ++j )
{
std::string identifier = "serie_" + *it2 + "_acquis_" + *it++;
gdcm::IPPSorter ippsorter;
gdcm::Directory::FilenamesType ipplist((j)*filesPerAcqu+subfiles.begin(),(j+1)*filesPerAcqu+subfiles.begin());
ippsorter.SetComputeZSpacing( true );
if( !ippsorter.Sort( ipplist ) )
{
Error(QString("Failed to sort acquisition %1, ABORTING").arg(identifier.c_str()));
if(m_OutputFolderNameSet) logfile << "Failed to sort acquisition " << identifier.c_str() << " , Aborting\n";
continue;
}
const std::vector<std::string> & list = ippsorter.GetFilenames();
seriesFilenames.push_back(list);
seriesUIDs.push_back(identifier.c_str());
}
++it2;
}
// Hot Fix for Bug 14758, checking if no file is acuired.
if (nTotalAcquis < 1) // Test if zero, if true than error because no file was selected
{
Error("Nno files in acquisitions, ABORTING");
if(m_OutputFolderNameSet) logfile << "Nno files in acquisitions, ABORTING \n";
continue;
}
if(nfiles % nTotalAcquis != 0)
{
Error("Number of files per acquisition differs between series, ABORTING");
if(m_OutputFolderNameSet) logfile << "Number of files per acquisition differs between series, ABORTING \n";
continue;
}
int slices = nfiles/nTotalAcquis;
Status(QString("Series is composed of %1 different 3D volumes with %2 slices.").arg(nTotalAcquis).arg(slices));
if(m_OutputFolderNameSet) logfile << "Series is composed of " << nTotalAcquis << " different 3D volumes with " << slices << " slices\n";
// READING HEADER-INFOS
PrintMemoryUsage();
Status(QString("Reading Headers %1").arg(folderName));
if(m_OutputFolderNameSet) logfile << "Reading Headers "<< folderName.toStdString() << "\n";
mitk::DicomDiffusionImageHeaderReader::Pointer headerReader;
typedef short PixelValueType;
typedef mitk::DicomDiffusionImageReader< PixelValueType, 3 > VolumesReader;
VolumesReader::HeaderContainer inHeaders;
unsigned int size2 = seriesUIDs.size();
for ( unsigned int i = 0 ; i < size2 ; ++i )
{
// Hot Fix for Bug 14459, catching if no valid data in datafile.
try
{
Status(QString("Reading header image #%1/%2").arg(i+1).arg(size2));
headerReader = mitk::DicomDiffusionImageHeaderReader::New();
headerReader->SetSeriesDicomFilenames(seriesFilenames[i]);
headerReader->Update();
inHeaders.push_back(headerReader->GetOutput());
}
catch (mitk::Exception e)
{
Error("Could not read file header, ABORTING");
if(m_OutputFolderNameSet) logfile << e;
continue;
}
//Status(std::endl;
}
mitk::ProgressBar::GetInstance()->Progress();
// // GROUP HEADERS
// mitk::GroupDiffusionHeadersFilter::Pointer grouper
// = mitk::GroupDiffusionHeadersFilter::New();
// mitk::GroupDiffusionHeadersFilter::OutputType outHeaders;
// grouper->SetInput(inHeaders);
// grouper->Update();
// outHeaders = grouper->GetOutput();
// READ VOLUMES
PrintMemoryUsage();
if(m_OutputFolderNameSet) logfile << "Loading volumes\n";
Status(QString("Loading Volumes %1").arg(folderName));
VolumesReader::Pointer vReader = VolumesReader::New();
VolumesReader::HeaderContainer hc = inHeaders;
// hc.insert(hc.end(), outHeaders[1].begin(), outHeaders[1].end() );
// hc.insert(hc.end(), outHeaders[2].begin(), outHeaders[2].end() );
if(hc.size()>1)
{
vReader->SetHeaders(hc);
vReader->Update();
VolumesReader::OutputImageType::Pointer vecImage;
vecImage = vReader->GetOutput();
Status(QString("Volumes Loaded (%1)").arg(folderName));
// CONSTRUCT CONTAINER WITH DIRECTIONS
typedef vnl_vector_fixed< double, 3 > GradientDirectionType;
typedef itk::VectorContainer< unsigned int,
GradientDirectionType > GradientDirectionContainerType;
GradientDirectionContainerType::Pointer directions =
GradientDirectionContainerType::New();
std::vector<double> b_vals;
double maxb = 0;
for(unsigned int i=0; i<hc.size(); i++)
{
double bv = hc[i]->bValue;
if(maxb<bv)
{
maxb = bv;
}
b_vals.push_back(bv);
}
for(unsigned int i=0; i<hc.size(); i++)
{
vnl_vector_fixed<double, 3> vect = hc[i]->DiffusionVector;
// since some protocols provide a gradient direction of (0,0,0) in their dicom files when isotropic diffusion is assumed,
// the nrrd compatible way of storing b-values is not possible, so in this case we overwrite
// the gradient direction to (1,1,1)
if (b_vals[i] > 0 && vect[0] == 0.0 && vect[1] == 0.0 && vect[2] ==0.0)
{
vect.fill(1.0);
}
vect.normalize();
vect *= sqrt(b_vals[i]/maxb);
directions->push_back(vect);
}
// DWI TO DATATREE
PrintMemoryUsage();
Status(QString("Initializing Diffusion Image"));
if(m_OutputFolderNameSet) logfile << "Initializing Diffusion Image\n";
typedef mitk::DiffusionImage<PixelValueType> DiffVolumesType;
DiffVolumesType::Pointer diffImage = DiffVolumesType::New();
diffImage->SetDirections(directions);
diffImage->SetVectorImage(vecImage);
diffImage->SetB_Value(maxb);
diffImage->InitializeFromVectorImage();
diffImage->UpdateBValueMap();
Status(QString("Diffusion Image initialized"));
if(m_OutputFolderNameSet) logfile << "Diffusion Image initialized\n";
if(m_Controls->m_DicomLoadAverageDuplicatesCheckbox->isChecked())
{
PrintMemoryUsage();
Status(QString("Averaging gradient directions"));
logfile << "Averaging gradient directions\n";
diffImage->AverageRedundantGradients(m_Controls->m_Blur->value());
}
QString descr = QString("%1_%2_%3")
.arg(((inHeaders)[0])->seriesDescription.c_str())
.arg(((inHeaders)[0])->seriesNumber)
.arg(((inHeaders)[0])->patientName.c_str());
descr = descr.trimmed();
descr = descr.replace(" ", "_");
if(!m_OutputFolderNameSet)
{
node=mitk::DataNode::New();
node->SetData( diffImage );
GetDefaultDataStorage()->Add(node);
SetDwiNodeProperties(node, descr.toStdString().c_str());
Status(QString("Image %1 added to datastorage").arg(descr));
}
else
{
typedef mitk::NrrdDiffusionImageWriter<PixelValueType> WriterType;
WriterType::Pointer writer = WriterType::New();
QString fullpath = QString("%1/%2.dwi")
.arg(m_OutputFolderName)
.arg(descr);
// if the override option is not checked, we need to make sure that the current filepath
// does not point to an existing file
if( !(m_Controls->m_OverrideOptionCheckbox->isChecked()) )
{
QFile outputFile( fullpath );
// generate new filename if file exists
int file_counter = 0;
while( outputFile.exists() )
{
// copy base name
QString newdescr = descr;
file_counter++;
MITK_WARN << "The file "<< fullpath.toStdString() << " exists already.";
QString appendix = QString("_%1").arg( QString::number(file_counter) );
newdescr.append(appendix);
fullpath = QString("%1/%2.dwi")
.arg(m_OutputFolderName)
.arg(newdescr);
// set the new generated filename for next check
outputFile.setFileName( fullpath );
}
}
writer->SetFileName(fullpath.toStdString());
writer->SetInput(diffImage);
try
{
writer->Update();
}
catch (itk::ExceptionObject &ex)
{
imageSuccessfullySaved = false;
Error(QString("%1\n%2\n%3\n%4\n%5\n%6").arg(ex.GetNameOfClass()).arg(ex.GetFile()).arg(ex.GetLine()).arg(ex.GetLocation()).arg(ex.what()).arg(ex.GetDescription()));
logfile << QString("%1\n%2\n%3\n%4\n%5\n%6").arg(ex.GetNameOfClass()).arg(ex.GetFile()).arg(ex.GetLine()).arg(ex.GetLocation()).arg(ex.what()).arg(ex.GetDescription()).toStdString() << "\n";
node=mitk::DataNode::New();
node->SetData( diffImage );
GetDefaultDataStorage()->Add(node);
SetDwiNodeProperties(node, descr.toStdString().c_str());
Status(QString("Image %1 added to datastorage").arg(descr));
logfile << "Image " << descr.toStdString() << " added to datastorage\n";
continue ;
}
Status(QString("Image %1 written to disc (%1)").arg(fullpath.toStdString().c_str()));
logfile << "Image " << fullpath.toStdString() << "\n";
}
}
else
{
Status(QString("No diffusion information found (%1)").arg(folderName));
if(m_OutputFolderNameSet) logfile << "No diffusion information found "<< folderName.toStdString();
}
Status(QString("Finished processing %1 with memory:").arg(folderName));
if(m_OutputFolderNameSet) logfile << "Finished processing " << folderName.toStdString() << "\n";
PrintMemoryUsage();
clock.Stop(folderName.toAscii());
mitk::ProgressBar::GetInstance()->Progress();
int lwidget = m_Controls->listWidget->count();
std::cout << lwidget <<std::endl;
logfile << "\n";
}
logfile.close();
Status("Timing information");
clock.Report();
if(!m_OutputFolderNameSet && node.IsNotNull())
{
mitk::BaseData::Pointer basedata = node->GetData();
if (basedata.IsNotNull())
{
mitk::RenderingManager::GetInstance()->InitializeViews(
basedata->GetTimeGeometry(), mitk::RenderingManager::REQUEST_UPDATE_ALL, true );
}
}
mitk::RenderingManager::GetInstance()->RequestUpdateAll();
try
{
MITK_INFO << " ** Changing locale back from " << setlocale(LC_ALL, NULL) << " to '" << currLocale << "'";
setlocale(LC_ALL, currLocale.c_str());
}
catch(...)
{
MITK_INFO << "Could not reset locale " << currLocale;
}
}
catch (itk::ExceptionObject &ex)
{
Error(QString("%1\n%2\n%3\n%4\n%5\n%6").arg(ex.GetNameOfClass()).arg(ex.GetFile()).arg(ex.GetLine()).arg(ex.GetLocation()).arg(ex.what()).arg(ex.GetDescription()));
return ;
}
if (!imageSuccessfullySaved)
QMessageBox::warning(NULL,"WARNING","One or more files could not be saved! The according files where moved to the datastorage.");
Status(QString("Finished import with memory:"));
PrintMemoryUsage();
}
void QmitkBasicImageProcessing::StartButtonClicked()
{
if(!m_SelectedImageNode->GetNode()) return;
this->BusyCursorOn();
mitk::Image::Pointer newImage;
try
{
newImage = dynamic_cast<mitk::Image*>(m_SelectedImageNode->GetNode()->GetData());
}
catch ( std::exception &e )
{
QString exceptionString = "An error occured during image loading:\n";
exceptionString.append( e.what() );
QMessageBox::warning( NULL, "Basic Image Processing", exceptionString , QMessageBox::Ok, QMessageBox::NoButton );
this->BusyCursorOff();
return;
}
// check if input image is valid, casting does not throw exception when casting from 'NULL-Object'
if ( (! newImage) || (newImage->IsInitialized() == false) )
{
this->BusyCursorOff();
QMessageBox::warning( NULL, "Basic Image Processing", "Input image is broken or not initialized. Returning.", QMessageBox::Ok, QMessageBox::NoButton );
return;
}
// check if operation is done on 4D a image time step
if(newImage->GetDimension() > 3)
{
mitk::ImageTimeSelector::Pointer timeSelector = mitk::ImageTimeSelector::New();
timeSelector->SetInput(newImage);
timeSelector->SetTimeNr( ((QmitkSliderNavigatorWidget*)m_Controls->sliceNavigatorTime)->GetPos() );
timeSelector->Update();
newImage = timeSelector->GetOutput();
}
// check if image or vector image
ImageType::Pointer itkImage = ImageType::New();
VectorImageType::Pointer itkVecImage = VectorImageType::New();
int isVectorImage = newImage->GetPixelType().GetNumberOfComponents();
if(isVectorImage > 1)
{
CastToItkImage( newImage, itkVecImage );
}
else
{
CastToItkImage( newImage, itkImage );
}
std::stringstream nameAddition("");
int param1 = m_Controls->sbParam1->value();
int param2 = m_Controls->sbParam2->value();
double dparam1 = m_Controls->dsbParam1->value();
double dparam2 = m_Controls->dsbParam2->value();
double dparam3 = m_Controls->dsbParam3->value();
try{
switch (m_SelectedAction)
{
case GAUSSIAN:
{
GaussianFilterType::Pointer gaussianFilter = GaussianFilterType::New();
gaussianFilter->SetInput( itkImage );
gaussianFilter->SetVariance( param1 );
gaussianFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(gaussianFilter->GetOutput())->Clone();
nameAddition << "_Gaussian_var_" << param1;
std::cout << "Gaussian filtering successful." << std::endl;
break;
}
case MEDIAN:
{
MedianFilterType::Pointer medianFilter = MedianFilterType::New();
MedianFilterType::InputSizeType size;
size.Fill(param1);
medianFilter->SetRadius( size );
medianFilter->SetInput(itkImage);
medianFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(medianFilter->GetOutput())->Clone();
nameAddition << "_Median_radius_" << param1;
std::cout << "Median Filtering successful." << std::endl;
break;
}
case TOTALVARIATION:
{
if(isVectorImage > 1)
{
VectorTotalVariationFilterType::Pointer TVFilter
= VectorTotalVariationFilterType::New();
TVFilter->SetInput( itkVecImage.GetPointer() );
TVFilter->SetNumberIterations(param1);
TVFilter->SetLambda(double(param2)/1000.);
TVFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(TVFilter->GetOutput())->Clone();
}
else
{
ImagePTypeToFloatPTypeCasterType::Pointer floatCaster = ImagePTypeToFloatPTypeCasterType::New();
floatCaster->SetInput( itkImage );
floatCaster->Update();
FloatImageType::Pointer fImage = floatCaster->GetOutput();
TotalVariationFilterType::Pointer TVFilter
= TotalVariationFilterType::New();
TVFilter->SetInput( fImage.GetPointer() );
TVFilter->SetNumberIterations(param1);
TVFilter->SetLambda(double(param2)/1000.);
TVFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(TVFilter->GetOutput())->Clone();
}
nameAddition << "_TV_Iter_" << param1 << "_L_" << param2;
std::cout << "Total Variation Filtering successful." << std::endl;
break;
}
case DILATION:
{
BallType binaryBall;
binaryBall.SetRadius( param1 );
binaryBall.CreateStructuringElement();
DilationFilterType::Pointer dilationFilter = DilationFilterType::New();
dilationFilter->SetInput( itkImage );
dilationFilter->SetKernel( binaryBall );
dilationFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(dilationFilter->GetOutput())->Clone();
nameAddition << "_Dilated_by_" << param1;
std::cout << "Dilation successful." << std::endl;
break;
}
case EROSION:
{
BallType binaryBall;
binaryBall.SetRadius( param1 );
binaryBall.CreateStructuringElement();
ErosionFilterType::Pointer erosionFilter = ErosionFilterType::New();
erosionFilter->SetInput( itkImage );
erosionFilter->SetKernel( binaryBall );
erosionFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(erosionFilter->GetOutput())->Clone();
nameAddition << "_Eroded_by_" << param1;
std::cout << "Erosion successful." << std::endl;
break;
}
case OPENING:
{
BallType binaryBall;
binaryBall.SetRadius( param1 );
binaryBall.CreateStructuringElement();
OpeningFilterType::Pointer openFilter = OpeningFilterType::New();
openFilter->SetInput( itkImage );
openFilter->SetKernel( binaryBall );
openFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(openFilter->GetOutput())->Clone();
nameAddition << "_Opened_by_" << param1;
std::cout << "Opening successful." << std::endl;
break;
}
case CLOSING:
{
BallType binaryBall;
binaryBall.SetRadius( param1 );
binaryBall.CreateStructuringElement();
ClosingFilterType::Pointer closeFilter = ClosingFilterType::New();
closeFilter->SetInput( itkImage );
closeFilter->SetKernel( binaryBall );
closeFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(closeFilter->GetOutput())->Clone();
nameAddition << "_Closed_by_" << param1;
std::cout << "Closing successful." << std::endl;
break;
}
case GRADIENT:
{
GradientFilterType::Pointer gradientFilter = GradientFilterType::New();
gradientFilter->SetInput( itkImage );
gradientFilter->SetSigma( param1 );
gradientFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(gradientFilter->GetOutput())->Clone();
nameAddition << "_Gradient_sigma_" << param1;
std::cout << "Gradient calculation successful." << std::endl;
break;
}
case LAPLACIAN:
{
// the laplace filter requires a float type image as input, we need to cast the itkImage
// to correct type
ImagePTypeToFloatPTypeCasterType::Pointer caster = ImagePTypeToFloatPTypeCasterType::New();
caster->SetInput( itkImage );
caster->Update();
FloatImageType::Pointer fImage = caster->GetOutput();
LaplacianFilterType::Pointer laplacianFilter = LaplacianFilterType::New();
laplacianFilter->SetInput( fImage );
laplacianFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(laplacianFilter->GetOutput())->Clone();
nameAddition << "_Second_Derivative";
std::cout << "Laplacian filtering successful." << std::endl;
break;
}
case SOBEL:
{
// the sobel filter requires a float type image as input, we need to cast the itkImage
// to correct type
ImagePTypeToFloatPTypeCasterType::Pointer caster = ImagePTypeToFloatPTypeCasterType::New();
caster->SetInput( itkImage );
caster->Update();
FloatImageType::Pointer fImage = caster->GetOutput();
SobelFilterType::Pointer sobelFilter = SobelFilterType::New();
sobelFilter->SetInput( fImage );
sobelFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(sobelFilter->GetOutput())->Clone();
nameAddition << "_Sobel";
std::cout << "Edge Detection successful." << std::endl;
break;
}
case THRESHOLD:
{
ThresholdFilterType::Pointer thFilter = ThresholdFilterType::New();
thFilter->SetLowerThreshold(param1 < param2 ? param1 : param2);
thFilter->SetUpperThreshold(param2 > param1 ? param2 : param1);
thFilter->SetInsideValue(1);
thFilter->SetOutsideValue(0);
thFilter->SetInput(itkImage);
thFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(thFilter->GetOutput())->Clone();
nameAddition << "_Threshold";
std::cout << "Thresholding successful." << std::endl;
break;
}
case INVERSION:
{
InversionFilterType::Pointer invFilter = InversionFilterType::New();
mitk::ScalarType min = newImage->GetScalarValueMin();
mitk::ScalarType max = newImage->GetScalarValueMax();
invFilter->SetMaximum( max + min );
invFilter->SetInput(itkImage);
invFilter->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(invFilter->GetOutput())->Clone();
nameAddition << "_Inverted";
std::cout << "Image inversion successful." << std::endl;
break;
}
case DOWNSAMPLING:
{
ResampleImageFilterType::Pointer downsampler = ResampleImageFilterType::New();
downsampler->SetInput( itkImage );
NearestInterpolatorType::Pointer interpolator = NearestInterpolatorType::New();
downsampler->SetInterpolator( interpolator );
downsampler->SetDefaultPixelValue( 0 );
ResampleImageFilterType::SpacingType spacing = itkImage->GetSpacing();
spacing *= (double) param1;
downsampler->SetOutputSpacing( spacing );
downsampler->SetOutputOrigin( itkImage->GetOrigin() );
downsampler->SetOutputDirection( itkImage->GetDirection() );
ResampleImageFilterType::SizeType size = itkImage->GetLargestPossibleRegion().GetSize();
for ( int i = 0; i < 3; ++i )
{
size[i] /= param1;
}
downsampler->SetSize( size );
downsampler->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(downsampler->GetOutput())->Clone();
nameAddition << "_Downsampled_by_" << param1;
std::cout << "Downsampling successful." << std::endl;
break;
}
case FLIPPING:
{
FlipImageFilterType::Pointer flipper = FlipImageFilterType::New();
flipper->SetInput( itkImage );
itk::FixedArray<bool, 3> flipAxes;
for(int i=0; i<3; ++i)
{
if(i == param1)
{
flipAxes[i] = true;
}
else
{
flipAxes[i] = false;
}
}
flipper->SetFlipAxes(flipAxes);
flipper->UpdateLargestPossibleRegion();
newImage = mitk::ImportItkImage(flipper->GetOutput())->Clone();
std::cout << "Image flipping successful." << std::endl;
break;
}
case RESAMPLING:
{
std::string selectedInterpolator;
ResampleImageFilterType::Pointer resampler = ResampleImageFilterType::New();
switch (m_SelectedInterpolation)
{
case LINEAR:
{
LinearInterpolatorType::Pointer interpolator = LinearInterpolatorType::New();
resampler->SetInterpolator(interpolator);
selectedInterpolator = "Linear";
break;
}
case NEAREST:
{
NearestInterpolatorType::Pointer interpolator = NearestInterpolatorType::New();
resampler->SetInterpolator(interpolator);
selectedInterpolator = "Nearest";
break;
}
default:
{
LinearInterpolatorType::Pointer interpolator = LinearInterpolatorType::New();
resampler->SetInterpolator(interpolator);
selectedInterpolator = "Linear";
break;
}
}
resampler->SetInput( itkImage );
resampler->SetOutputOrigin( itkImage->GetOrigin() );
ImageType::SizeType input_size = itkImage->GetLargestPossibleRegion().GetSize();
ImageType::SpacingType input_spacing = itkImage->GetSpacing();
ImageType::SizeType output_size;
ImageType::SpacingType output_spacing;
output_size[0] = input_size[0] * (input_spacing[0] / dparam1);
output_size[1] = input_size[1] * (input_spacing[1] / dparam2);
output_size[2] = input_size[2] * (input_spacing[2] / dparam3);
output_spacing [0] = dparam1;
output_spacing [1] = dparam2;
output_spacing [2] = dparam3;
resampler->SetSize( output_size );
resampler->SetOutputSpacing( output_spacing );
resampler->SetOutputDirection( itkImage->GetDirection() );
resampler->UpdateLargestPossibleRegion();
ImageType::Pointer resampledImage = resampler->GetOutput();
newImage = mitk::ImportItkImage( resampledImage );
nameAddition << "_Resampled_" << selectedInterpolator;
std::cout << "Resampling successful." << std::endl;
break;
}
case RESCALE:
{
FloatImageType::Pointer floatImage = FloatImageType::New();
CastToItkImage( newImage, floatImage );
itk::RescaleIntensityImageFilter<FloatImageType,FloatImageType>::Pointer filter = itk::RescaleIntensityImageFilter<FloatImageType,FloatImageType>::New();
filter->SetInput(0, floatImage);
filter->SetOutputMinimum(dparam1);
filter->SetOutputMaximum(dparam2);
filter->Update();
floatImage = filter->GetOutput();
newImage = mitk::Image::New();
newImage->InitializeByItk(floatImage.GetPointer());
newImage->SetVolume(floatImage->GetBufferPointer());
nameAddition << "_Rescaled";
std::cout << "Rescaling successful." << std::endl;
break;
}
default:
this->BusyCursorOff();
return;
}
}
catch (...)
{
this->BusyCursorOff();
QMessageBox::warning(NULL, "Warning", "Problem when applying filter operation. Check your input...");
return;
}
newImage->DisconnectPipeline();
// adjust level/window to new image
mitk::LevelWindow levelwindow;
levelwindow.SetAuto( newImage );
mitk::LevelWindowProperty::Pointer levWinProp = mitk::LevelWindowProperty::New();
levWinProp->SetLevelWindow( levelwindow );
// compose new image name
std::string name = m_SelectedImageNode->GetNode()->GetName();
if (name.find(".pic.gz") == name.size() -7 )
{
name = name.substr(0,name.size() -7);
}
name.append( nameAddition.str() );
// create final result MITK data storage node
mitk::DataNode::Pointer result = mitk::DataNode::New();
result->SetProperty( "levelwindow", levWinProp );
result->SetProperty( "name", mitk::StringProperty::New( name.c_str() ) );
result->SetData( newImage );
// for vector images, a different mapper is needed
if(isVectorImage > 1)
{
mitk::VectorImageMapper2D::Pointer mapper =
mitk::VectorImageMapper2D::New();
result->SetMapper(1,mapper);
}
// reset GUI to ease further processing
// this->ResetOneImageOpPanel();
// add new image to data storage and set as active to ease further processing
GetDefaultDataStorage()->Add( result, m_SelectedImageNode->GetNode() );
if ( m_Controls->cbHideOrig->isChecked() == true )
m_SelectedImageNode->GetNode()->SetProperty( "visible", mitk::BoolProperty::New(false) );
// TODO!! m_Controls->m_ImageSelector1->SetSelectedNode(result);
// show the results
mitk::RenderingManager::GetInstance()->RequestUpdateAll();
this->BusyCursorOff();
}
void QmitkDenoisingView::StartDenoising()
{
if (!m_ThreadIsRunning)
{
if (m_ImageNode.IsNotNull())
{
m_LastProgressCount = 0;
switch (m_SelectedFilter)
{
case NOFILTERSELECTED:
{
break;
}
case NLM:
{
// initialize NLM
m_InputImage = dynamic_cast<DiffusionImageType*> (m_ImageNode->GetData());
m_NonLocalMeansFilter = NonLocalMeansDenoisingFilterType::New();
if (m_BrainMaskNode.IsNotNull())
{
// use brainmask if set
m_ImageMask = dynamic_cast<mitk::Image*>(m_BrainMaskNode->GetData());
itk::Image<DiffusionPixelType, 3>::Pointer itkMask;
mitk::CastToItkImage(m_ImageMask, itkMask);
m_NonLocalMeansFilter->SetInputMask(itkMask);
itk::ImageRegionIterator< itk::Image<DiffusionPixelType, 3> > mit(itkMask, itkMask->GetLargestPossibleRegion());
mit.GoToBegin();
itk::Image<DiffusionPixelType, 3>::IndexType minIndex;
itk::Image<DiffusionPixelType, 3>::IndexType maxIndex;
minIndex.Fill(10000);
maxIndex.Fill(0);
while (!mit.IsAtEnd())
{
if (mit.Get())
{
// calculation of the start & end index of the smallest masked region
minIndex[0] = minIndex[0] < mit.GetIndex()[0] ? minIndex[0] : mit.GetIndex()[0];
minIndex[1] = minIndex[1] < mit.GetIndex()[1] ? minIndex[1] : mit.GetIndex()[1];
minIndex[2] = minIndex[2] < mit.GetIndex()[2] ? minIndex[2] : mit.GetIndex()[2];
maxIndex[0] = maxIndex[0] > mit.GetIndex()[0] ? maxIndex[0] : mit.GetIndex()[0];
maxIndex[1] = maxIndex[1] > mit.GetIndex()[1] ? maxIndex[1] : mit.GetIndex()[1];
maxIndex[2] = maxIndex[2] > mit.GetIndex()[2] ? maxIndex[2] : mit.GetIndex()[2];
}
++mit;
}
itk::Image<DiffusionPixelType, 3>::SizeType size;
size[0] = maxIndex[0] - minIndex[0] + 1;
size[1] = maxIndex[1] - minIndex[1] + 1;
size[2] = maxIndex[2] - minIndex[2] + 1;
m_MaxProgressCount = size[0] * size[1] * size[2];
}
else
{
// initialize the progressbar
m_MaxProgressCount = m_InputImage->GetDimension(0) * m_InputImage->GetDimension(1) * m_InputImage->GetDimension(2);
}
mitk::ProgressBar::GetInstance()->AddStepsToDo(m_MaxProgressCount);
m_NonLocalMeansFilter->SetInputImage(m_InputImage->GetVectorImage());
m_NonLocalMeansFilter->SetUseRicianAdaption(m_Controls->m_RicianCheckbox->isChecked());
m_NonLocalMeansFilter->SetUseJointInformation(m_Controls->m_JointInformationCheckbox->isChecked());
m_NonLocalMeansFilter->SetSearchRadius(m_Controls->m_SpinBoxParameter1->value());
m_NonLocalMeansFilter->SetComparisonRadius(m_Controls->m_SpinBoxParameter2->value());
m_NonLocalMeansFilter->SetVariance(m_Controls->m_DoubleSpinBoxParameter3->value());
// start denoising in detached thread
m_DenoisingThread.start(QThread::HighestPriority);
break;
}
case GAUSS:
{
// initialize GAUSS and run
m_InputImage = dynamic_cast<DiffusionImageType*> (m_ImageNode->GetData());
ExtractFilterType::Pointer extractor = ExtractFilterType::New();
extractor->SetInput(m_InputImage->GetVectorImage());
ComposeFilterType::Pointer composer = ComposeFilterType::New();
for (unsigned int i = 0; i < m_InputImage->GetVectorImage()->GetVectorLength(); ++i)
{
extractor->SetIndex(i);
extractor->Update();
m_GaussianFilter = GaussianFilterType::New();
m_GaussianFilter->SetVariance(m_Controls->m_SpinBoxParameter1->value());
if (m_BrainMaskNode.IsNotNull())
{
m_ImageMask = dynamic_cast<mitk::Image*>(m_BrainMaskNode->GetData());
itk::Image<DiffusionPixelType, 3>::Pointer itkMask = itk::Image<DiffusionPixelType, 3>::New();
mitk::CastToItkImage(m_ImageMask, itkMask);
itk::MaskImageFilter<itk::Image<DiffusionPixelType, 3> , itk::Image<DiffusionPixelType, 3> >::Pointer maskImageFilter = itk::MaskImageFilter<itk::Image<DiffusionPixelType, 3> , itk::Image<DiffusionPixelType, 3> >::New();
maskImageFilter->SetInput(extractor->GetOutput());
maskImageFilter->SetMaskImage(itkMask);
maskImageFilter->Update();
m_GaussianFilter->SetInput(maskImageFilter->GetOutput());
}
else
{
m_GaussianFilter->SetInput(extractor->GetOutput());
}
m_GaussianFilter->Update();
composer->SetInput(i, m_GaussianFilter->GetOutput());
}
composer->Update();
DiffusionImageType::Pointer image = DiffusionImageType::New();
image->SetVectorImage(composer->GetOutput());
image->SetReferenceBValue(m_InputImage->GetReferenceBValue());
image->SetDirections(m_InputImage->GetDirections());
image->InitializeFromVectorImage();
mitk::DataNode::Pointer imageNode = mitk::DataNode::New();
imageNode->SetData( image );
QString name = m_ImageNode->GetName().c_str();
imageNode->SetName((name+"_gauss_"+QString::number(m_Controls->m_SpinBoxParameter1->value())).toStdString().c_str());
GetDefaultDataStorage()->Add(imageNode);
break;
}
}
}
}
else
{
m_NonLocalMeansFilter->AbortGenerateDataOn();
m_CompletedCalculation = false;
}
}
