// -----------------------------------------------------------------------------
//
// -----------------------------------------------------------------------------
void SobelEdge::execute()
{
dataCheck();
if(getErrorCondition() < 0) { return; }
DataContainer::Pointer m = getDataContainerArray()->getDataContainer(getSelectedCellArrayPath().getDataContainerName());
QString attrMatName = getSelectedCellArrayPath().getAttributeMatrixName();
//wrap m_RawImageData as itk::image
ImageProcessing::DefaultImageType::Pointer inputImage = ITKUtilitiesType::CreateItkWrapperForDataPointer(m, attrMatName, m_SelectedCellArray);
if(m_Slice)
{
//wrap output array
ImageProcessing::DefaultImageType::Pointer outputImage = ITKUtilitiesType::CreateItkWrapperForDataPointer(m, attrMatName, m_NewCellArray);
//get dimensions
size_t udims[3] = {0, 0, 0};
m->getGeometryAs<ImageGeom>()->getDimensions(udims);
#if (CMP_SIZEOF_SIZE_T == 4)
typedef int32_t DimType;
#else
typedef int64_t DimType;
#endif
DimType dims[3] =
{
static_cast<DimType>(udims[0]),
static_cast<DimType>(udims[1]),
static_cast<DimType>(udims[2]),
};
//create edge filter
typedef itk::SobelEdgeDetectionImageFilter<ImageProcessing::DefaultSliceType, ImageProcessing::FloatSliceType> SobelFilterType;
SobelFilterType::Pointer sobelFilter = SobelFilterType::New();
//convert result back to uint8
typedef itk::RescaleIntensityImageFilter<ImageProcessing::FloatSliceType, ImageProcessing::DefaultSliceType> RescaleImageType;
RescaleImageType::Pointer rescaleFilter = RescaleImageType::New();
rescaleFilter->SetOutputMinimum(0);
rescaleFilter->SetOutputMaximum(255);
//loop over slices applying filters
for(int i = 0; i < dims[2]; ++i)
{
QString ss = QObject::tr("Finding Edges On Slice: %1").arg(i + 1);
notifyStatusMessage(getMessagePrefix(), getHumanLabel(), ss);
//get slice
ImageProcessing::DefaultSliceType::Pointer inputSlice = ITKUtilitiesType::ExtractSlice(inputImage, ImageProcessing::ZSlice, i);
//run filters
sobelFilter->SetInput(inputSlice);
rescaleFilter->SetInput(sobelFilter->GetOutput());
//execute filters
try
{
sobelFilter->Update();
rescaleFilter->Update();
}
catch( itk::ExceptionObject& err )
{
setErrorCondition(-5);
QString ss = QObject::tr("Failed to execute itk::SobelEdgeDetectionImageFilter filter. Error Message returned from ITK:\n %1").arg(err.GetDescription());
notifyErrorMessage(getHumanLabel(), ss, getErrorCondition());
}
//copy into volume
ITKUtilitiesType::SetSlice(outputImage, rescaleFilter->GetOutput(), ImageProcessing::ZSlice, i);
}
}
else
{
//create edge filter
typedef itk::SobelEdgeDetectionImageFilter<ImageProcessing::DefaultImageType, ImageProcessing::FloatImageType> SobelFilterType;
SobelFilterType::Pointer sobelFilter = SobelFilterType::New();
sobelFilter->SetInput(inputImage);
//convert result back to uint8
typedef itk::RescaleIntensityImageFilter<ImageProcessing::FloatImageType, ImageProcessing::DefaultImageType> RescaleImageType;
RescaleImageType::Pointer rescaleFilter = RescaleImageType::New();
rescaleFilter->SetInput(sobelFilter->GetOutput());
rescaleFilter->SetOutputMinimum(0);
rescaleFilter->SetOutputMaximum(255);
//have filter write to dream3d array instead of creating its own buffer
ITKUtilitiesType::SetITKFilterOutput(rescaleFilter->GetOutput(), m_NewCellArrayPtr.lock());
//execute filters
try
{
sobelFilter->Update();
rescaleFilter->Update();
}
catch( itk::ExceptionObject& err )
{
setErrorCondition(-5);
QString ss = QObject::tr("Failed to execute itk::SobelEdgeDetectionImageFilter filter. Error Message returned from ITK:\n %1").arg(err.GetDescription());
notifyErrorMessage(getHumanLabel(), ss, getErrorCondition());
}
}
//array name changing/cleanup
if(m_SaveAsNewArray == false)
{
AttributeMatrix::Pointer attrMat = m->getAttributeMatrix(m_SelectedCellArrayPath.getAttributeMatrixName());
attrMat->removeAttributeArray(m_SelectedCellArrayPath.getDataArrayName());
attrMat->renameAttributeArray(m_NewCellArrayName, m_SelectedCellArrayPath.getDataArrayName());
}
/* Let the GUI know we are done with this filter */
notifyStatusMessage(getHumanLabel(), "Complete");
}
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();
}
