void DicomDiffusionImageReader<TPixelType, TDimension>
::GenerateOutputInformation(void)
{
typename OutputImageType::Pointer output = this->GetOutput();
typedef itk::ImageSeriesReader<InputImageType> ReaderType;
// Read the first (or last) volume and use its size.
if (m_Headers.size() > 0)
{
typename ReaderType::Pointer reader = ReaderType::New();
try
{
// Read the image
reader->SetFileNames (m_Headers[0]->m_DicomFilenames);
reader->UpdateOutputInformation();
output->SetSpacing( reader->GetOutput()->GetSpacing() ); // Set the image spacing
output->SetOrigin( reader->GetOutput()->GetOrigin() ); // Set the image origin
output->SetDirection( reader->GetOutput()->GetDirection() ); // Set the image direction
output->SetLargestPossibleRegion( reader->GetOutput()->GetLargestPossibleRegion() );
output->SetVectorLength( m_Headers.size() );
}
catch (itk::ExceptionObject &e)
{
throw e;
}
}
else
{
itkExceptionMacro(<< "At least one filename is required." );
}
}
DwiPhantomGenerationFilter< TOutputScalarType >
::DwiPhantomGenerationFilter()
: m_BValue(1000)
, m_SignalScale(1000)
, m_BaselineImages(0)
, m_MaxBaseline(0)
, m_MeanBaseline(0)
, m_NoiseVariance(0.004)
, m_GreyMatterAdc(0.01)
, m_SimulateBaseline(true)
, m_DefaultBaseline(1000)
{
this->SetNumberOfRequiredOutputs (1);
m_Spacing.Fill(2.5); m_Origin.Fill(0.0);
m_DirectionMatrix.SetIdentity();
m_ImageRegion.SetSize(0, 10);
m_ImageRegion.SetSize(1, 10);
m_ImageRegion.SetSize(2, 10);
typename OutputImageType::Pointer outImage = OutputImageType::New();
outImage->SetSpacing( m_Spacing ); // Set the image spacing
outImage->SetOrigin( m_Origin ); // Set the image origin
outImage->SetDirection( m_DirectionMatrix ); // Set the image direction
outImage->SetLargestPossibleRegion( m_ImageRegion );
outImage->SetBufferedRegion( m_ImageRegion );
outImage->SetRequestedRegion( m_ImageRegion );
outImage->SetVectorLength(QBALL_ODFSIZE);
outImage->Allocate();
outImage->FillBuffer(0);
this->SetNthOutput (0, outImage);
}
void FieldmapGeneratorFilter< OutputImageType >::BeforeThreadedGenerateData()
{
typename OutputImageType::Pointer outImage = OutputImageType::New();
outImage->SetSpacing( m_Spacing );
outImage->SetOrigin( m_Origin );
outImage->SetDirection( m_DirectionMatrix );
outImage->SetLargestPossibleRegion( m_ImageRegion );
outImage->SetBufferedRegion( m_ImageRegion );
outImage->SetRequestedRegion( m_ImageRegion );
outImage->Allocate();
outImage->FillBuffer(0);
this->SetNthOutput(0, outImage);
}
void DwiPhantomGenerationFilter< TOutputScalarType >
::GenerateData()
{
if (m_NoiseVariance < 0)
m_NoiseVariance = 0.001;
if (!m_SimulateBaseline)
{
MITK_INFO << "Baseline image values are set to default. Noise variance value is treated as SNR!";
if (m_NoiseVariance <= 0)
m_NoiseVariance = 0.0001;
if (m_NoiseVariance>99)
m_NoiseVariance = 0;
else
{
m_NoiseVariance = m_DefaultBaseline/(m_NoiseVariance*m_SignalScale);
m_NoiseVariance *= m_NoiseVariance;
}
}
m_RandGen = Statistics::MersenneTwisterRandomVariateGenerator::New();
m_RandGen->SetSeed();
typename OutputImageType::Pointer outImage = OutputImageType::New();
outImage->SetSpacing( m_Spacing );
outImage->SetOrigin( m_Origin );
outImage->SetDirection( m_DirectionMatrix );
outImage->SetLargestPossibleRegion( m_ImageRegion );
outImage->SetBufferedRegion( m_ImageRegion );
outImage->SetRequestedRegion( m_ImageRegion );
outImage->SetVectorLength(m_GradientList.size());
outImage->Allocate();
typename OutputImageType::PixelType pix;
pix.SetSize(m_GradientList.size());
pix.Fill(0.0);
outImage->FillBuffer(pix);
this->SetNthOutput (0, outImage);
double minSpacing = m_Spacing[0];
if (m_Spacing[1]<minSpacing)
minSpacing = m_Spacing[1];
if (m_Spacing[2]<minSpacing)
minSpacing = m_Spacing[2];
m_DirectionImageContainer = ItkDirectionImageContainer::New();
for (int i=0; i<m_SignalRegions.size(); i++)
{
itk::Vector< float, 3 > nullVec; nullVec.Fill(0.0);
ItkDirectionImage::Pointer img = ItkDirectionImage::New();
img->SetSpacing( m_Spacing );
img->SetOrigin( m_Origin );
img->SetDirection( m_DirectionMatrix );
img->SetRegions( m_ImageRegion );
img->Allocate();
img->FillBuffer(nullVec);
m_DirectionImageContainer->InsertElement(m_DirectionImageContainer->Size(), img);
}
m_NumDirectionsImage = ItkUcharImgType::New();
m_NumDirectionsImage->SetSpacing( m_Spacing );
m_NumDirectionsImage->SetOrigin( m_Origin );
m_NumDirectionsImage->SetDirection( m_DirectionMatrix );
m_NumDirectionsImage->SetRegions( m_ImageRegion );
m_NumDirectionsImage->Allocate();
m_NumDirectionsImage->FillBuffer(0);
m_SNRImage = ItkFloatImgType::New();
m_SNRImage->SetSpacing( m_Spacing );
m_SNRImage->SetOrigin( m_Origin );
m_SNRImage->SetDirection( m_DirectionMatrix );
m_SNRImage->SetRegions( m_ImageRegion );
m_SNRImage->Allocate();
m_SNRImage->FillBuffer(0);
vtkSmartPointer<vtkCellArray> m_VtkCellArray = vtkSmartPointer<vtkCellArray>::New();
vtkSmartPointer<vtkPoints> m_VtkPoints = vtkSmartPointer<vtkPoints>::New();
m_BaselineImages = 0;
for( unsigned int i=0; i<m_GradientList.size(); i++)
if (m_GradientList[i].GetNorm()<=0.0001)
m_BaselineImages++;
typedef ImageRegionIterator<OutputImageType> IteratorOutputType;
IteratorOutputType it (outImage, m_ImageRegion);
// isotropic tensor
itk::DiffusionTensor3D<float> isoTensor;
isoTensor.Fill(0);
float e1 = m_GreyMatterAdc;
float e2 = m_GreyMatterAdc;
float e3 = m_GreyMatterAdc;
isoTensor.SetElement(0,e1);
isoTensor.SetElement(3,e2);
isoTensor.SetElement(5,e3);
m_MaxBaseline = GetTensorL2Norm(isoTensor);
GenerateTensors();
// simulate measurement
m_MeanBaseline = 0;
double noiseStdev = sqrt(m_NoiseVariance);
while(!it.IsAtEnd())
{
pix = it.Get();
typename OutputImageType::IndexType index = it.GetIndex();
int numDirs = 0;
for (int i=0; i<m_SignalRegions.size(); i++)
{
ItkUcharImgType::Pointer region = m_SignalRegions.at(i);
if (region->GetPixel(index)!=0)
{
numDirs++;
pix += SimulateMeasurement(m_TensorList[i], m_TensorWeight[i]);
// set direction image pixel
ItkDirectionImage::Pointer img = m_DirectionImageContainer->GetElement(i);
itk::Vector< float, 3 > pixel = img->GetPixel(index);
vnl_vector_fixed<double, 3> dir = m_TensorDirection.at(i);
dir.normalize();
dir *= m_TensorWeight.at(i);
pixel.SetElement(0, dir[0]);
pixel.SetElement(1, dir[1]);
pixel.SetElement(2, dir[2]);
img->SetPixel(index, pixel);
vtkSmartPointer<vtkPolyLine> container = vtkSmartPointer<vtkPolyLine>::New();
itk::ContinuousIndex<double, 3> center;
center[0] = index[0];
center[1] = index[1];
center[2] = index[2];
itk::Point<double> worldCenter;
outImage->TransformContinuousIndexToPhysicalPoint( center, worldCenter );
itk::Point<double> worldStart;
worldStart[0] = worldCenter[0]-dir[0]/2 * minSpacing;
worldStart[1] = worldCenter[1]-dir[1]/2 * minSpacing;
worldStart[2] = worldCenter[2]-dir[2]/2 * minSpacing;
vtkIdType id = m_VtkPoints->InsertNextPoint(worldStart.GetDataPointer());
container->GetPointIds()->InsertNextId(id);
itk::Point<double> worldEnd;
worldEnd[0] = worldCenter[0]+dir[0]/2 * minSpacing;
worldEnd[1] = worldCenter[1]+dir[1]/2 * minSpacing;
worldEnd[2] = worldCenter[2]+dir[2]/2 * minSpacing;
id = m_VtkPoints->InsertNextPoint(worldEnd.GetDataPointer());
container->GetPointIds()->InsertNextId(id);
m_VtkCellArray->InsertNextCell(container);
}
}
if (numDirs>1)
{
for (int i=0; i<m_GradientList.size(); i++)
pix[i] /= numDirs;
}
else if (numDirs==0)
{
if (m_SimulateBaseline)
pix = SimulateMeasurement(isoTensor, 1.0);
else
pix.Fill(0.0);
}
m_MeanBaseline += pix[0];
it.Set(pix);
m_NumDirectionsImage->SetPixel(index, numDirs);
if (m_NoiseVariance>0)
m_SNRImage->SetPixel(index, pix[0]/(noiseStdev*m_SignalScale));
++it;
}
m_MeanBaseline /= m_ImageRegion.GetNumberOfPixels();
if (m_NoiseVariance>0)
MITK_INFO << "Mean SNR: " << m_MeanBaseline/(noiseStdev*m_SignalScale);
else
MITK_INFO << "No noise added";
// add rician noise
it.GoToBegin();
while(!it.IsAtEnd())
{
pix = it.Get();
AddNoise(pix);
it.Set(pix);
++it;
}
// generate fiber bundle
vtkSmartPointer<vtkPolyData> directionsPolyData = vtkSmartPointer<vtkPolyData>::New();
directionsPolyData->SetPoints(m_VtkPoints);
directionsPolyData->SetLines(m_VtkCellArray);
m_OutputFiberBundle = mitk::FiberBundleX::New(directionsPolyData);
}