diff --git a/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.cpp b/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.cpp index 18faff8edc..caef447cf8 100755 --- a/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.cpp +++ b/Modules/DiffusionImaging/FiberTracking/Algorithms/itkTractsToDWIImageFilter.cpp @@ -1,1237 +1,1238 @@ /*=================================================================== The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center, Division of Medical and Biological Informatics. All rights reserved. This software is distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See LICENSE.txt or http://www.mitk.org for details. ===================================================================*/ #include "itkTractsToDWIImageFilter.h" #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace itk { template< class PixelType > TractsToDWIImageFilter< PixelType >::TractsToDWIImageFilter() : m_FiberBundle(NULL) , m_StatusText("") , m_UseConstantRandSeed(false) , m_RandGen(itk::Statistics::MersenneTwisterRandomVariateGenerator::New()) { m_RandGen->SetSeed(); } template< class PixelType > TractsToDWIImageFilter< PixelType >::~TractsToDWIImageFilter() { } template< class PixelType > TractsToDWIImageFilter< PixelType >::DoubleDwiType::Pointer TractsToDWIImageFilter< PixelType >::DoKspaceStuff( std::vector< DoubleDwiType::Pointer >& images ) { int numFiberCompartments = m_Parameters.m_FiberModelList.size(); // create slice object ImageRegion<2> sliceRegion; sliceRegion.SetSize(0, m_UpsampledImageRegion.GetSize()[0]); sliceRegion.SetSize(1, m_UpsampledImageRegion.GetSize()[1]); Vector< double, 2 > sliceSpacing; sliceSpacing[0] = m_UpsampledSpacing[0]; sliceSpacing[1] = m_UpsampledSpacing[1]; // frequency map slice SliceType::Pointer fMapSlice = NULL; if (m_Parameters.m_FrequencyMap.IsNotNull()) { fMapSlice = SliceType::New(); ImageRegion<2> region; region.SetSize(0, m_UpsampledImageRegion.GetSize()[0]); region.SetSize(1, m_UpsampledImageRegion.GetSize()[1]); fMapSlice->SetLargestPossibleRegion( region ); fMapSlice->SetBufferedRegion( region ); fMapSlice->SetRequestedRegion( region ); fMapSlice->Allocate(); fMapSlice->FillBuffer(0.0); } DoubleDwiType::Pointer newImage = DoubleDwiType::New(); newImage->SetSpacing( m_Parameters.m_ImageSpacing ); newImage->SetOrigin( m_Parameters.m_ImageOrigin ); newImage->SetDirection( m_Parameters.m_ImageDirection ); newImage->SetLargestPossibleRegion( m_Parameters.m_ImageRegion ); newImage->SetBufferedRegion( m_Parameters.m_ImageRegion ); newImage->SetRequestedRegion( m_Parameters.m_ImageRegion ); newImage->SetVectorLength( images.at(0)->GetVectorLength() ); newImage->Allocate(); std::vector< unsigned int > spikeVolume; for (unsigned int i=0; iGetIntegerVariate()%images.at(0)->GetVectorLength()); std::sort (spikeVolume.begin(), spikeVolume.end()); std::reverse (spikeVolume.begin(), spikeVolume.end()); m_StatusText += "0% 10 20 30 40 50 60 70 80 90 100%\n"; m_StatusText += "|----|----|----|----|----|----|----|----|----|----|\n*"; unsigned long lastTick = 0; boost::progress_display disp(2*images.at(0)->GetVectorLength()*images.at(0)->GetLargestPossibleRegion().GetSize(2)); for (unsigned int g=0; gGetVectorLength(); g++) { std::vector< unsigned int > spikeSlice; while (!spikeVolume.empty() && spikeVolume.back()==g) { spikeSlice.push_back(m_RandGen->GetIntegerVariate()%images.at(0)->GetLargestPossibleRegion().GetSize(2)); spikeVolume.pop_back(); } std::sort (spikeSlice.begin(), spikeSlice.end()); std::reverse (spikeSlice.begin(), spikeSlice.end()); for (unsigned int z=0; zGetLargestPossibleRegion().GetSize(2); z++) { std::vector< SliceType::Pointer > compartmentSlices; std::vector< double > t2Vector; for (unsigned int i=0; i* signalModel; if (iSetLargestPossibleRegion( sliceRegion ); slice->SetBufferedRegion( sliceRegion ); slice->SetRequestedRegion( sliceRegion ); slice->SetSpacing(sliceSpacing); slice->Allocate(); slice->FillBuffer(0.0); // extract slice from channel g for (unsigned int y=0; yGetLargestPossibleRegion().GetSize(1); y++) for (unsigned int x=0; xGetLargestPossibleRegion().GetSize(0); x++) { SliceType::IndexType index2D; index2D[0]=x; index2D[1]=y; DoubleDwiType::IndexType index3D; index3D[0]=x; index3D[1]=y; index3D[2]=z; slice->SetPixel(index2D, images.at(i)->GetPixel(index3D)[g]); if (fMapSlice.IsNotNull() && i==0) fMapSlice->SetPixel(index2D, m_Parameters.m_FrequencyMap->GetPixel(index3D)); } compartmentSlices.push_back(slice); t2Vector.push_back(signalModel->GetT2()); } if (this->GetAbortGenerateData()) return NULL; // create k-sapce (inverse fourier transform slices) itk::Size<2> outSize; outSize.SetElement(0, m_Parameters.m_ImageRegion.GetSize(0)); outSize.SetElement(1, m_Parameters.m_ImageRegion.GetSize(1)); itk::KspaceImageFilter< SliceType::PixelType >::Pointer idft = itk::KspaceImageFilter< SliceType::PixelType >::New(); idft->SetCompartmentImages(compartmentSlices); idft->SetT2(t2Vector); idft->SetUseConstantRandSeed(m_UseConstantRandSeed); idft->SetParameters(m_Parameters); idft->SetZ((double)z-(double)images.at(0)->GetLargestPossibleRegion().GetSize(2)/2.0); idft->SetDiffusionGradientDirection(m_Parameters.GetGradientDirection(g)); idft->SetFrequencyMapSlice(fMapSlice); idft->SetOutSize(outSize); int numSpikes = 0; while (!spikeSlice.empty() && spikeSlice.back()==z) { numSpikes++; spikeSlice.pop_back(); } idft->SetSpikesPerSlice(numSpikes); idft->Update(); ComplexSliceType::Pointer fSlice; fSlice = idft->GetOutput(); ++disp; unsigned long newTick = 50*disp.count()/disp.expected_count(); for (unsigned long tick = 0; tick<(newTick-lastTick); tick++) m_StatusText += "*"; lastTick = newTick; // fourier transform slice SliceType::Pointer newSlice; itk::DftImageFilter< SliceType::PixelType >::Pointer dft = itk::DftImageFilter< SliceType::PixelType >::New(); dft->SetInput(fSlice); dft->Update(); newSlice = dft->GetOutput(); // put slice back into channel g for (unsigned int y=0; yGetLargestPossibleRegion().GetSize(1); y++) for (unsigned int x=0; xGetLargestPossibleRegion().GetSize(0); x++) { DoubleDwiType::IndexType index3D; index3D[0]=x; index3D[1]=y; index3D[2]=z; SliceType::IndexType index2D; index2D[0]=x; index2D[1]=y; DoubleDwiType::PixelType pix3D = newImage->GetPixel(index3D); pix3D[g] = newSlice->GetPixel(index2D); newImage->SetPixel(index3D, pix3D); } ++disp; newTick = 50*disp.count()/disp.expected_count(); for (unsigned long tick = 0; tick<(newTick-lastTick); tick++) m_StatusText += "*"; lastTick = newTick; } } m_StatusText += "\n\n"; return newImage; } template< class PixelType > void TractsToDWIImageFilter< PixelType >::GenerateData() { m_TimeProbe.Start(); m_StatusText = "Starting simulation\n"; // check input data if (m_FiberBundle.IsNull()) itkExceptionMacro("Input fiber bundle is NULL!"); if (m_Parameters.m_FiberModelList.empty()) itkExceptionMacro("No diffusion model for fiber compartments defined!"); if (m_Parameters.m_NonFiberModelList.empty()) itkExceptionMacro("No diffusion model for non-fiber compartments defined!"); int baselineIndex = m_Parameters.GetFirstBaselineIndex(); if (baselineIndex<0) itkExceptionMacro("No baseline index found!"); if (!m_Parameters.m_SimulateKspaceAcquisition) m_Parameters.m_DoAddGibbsRinging = false; if (m_UseConstantRandSeed) // always generate the same random numbers? m_RandGen->SetSeed(0); else m_RandGen->SetSeed(); // initialize output dwi image ImageRegion<3> croppedRegion = m_Parameters.m_ImageRegion; croppedRegion.SetSize(1, croppedRegion.GetSize(1)*m_Parameters.m_CroppingFactor); itk::Point shiftedOrigin = m_Parameters.m_ImageOrigin; shiftedOrigin[1] += (m_Parameters.m_ImageRegion.GetSize(1)-croppedRegion.GetSize(1))*m_Parameters.m_ImageSpacing[1]/2; typename OutputImageType::Pointer outImage = OutputImageType::New(); outImage->SetSpacing( m_Parameters.m_ImageSpacing ); outImage->SetOrigin( shiftedOrigin ); outImage->SetDirection( m_Parameters.m_ImageDirection ); outImage->SetLargestPossibleRegion( croppedRegion ); outImage->SetBufferedRegion( croppedRegion ); outImage->SetRequestedRegion( croppedRegion ); outImage->SetVectorLength( m_Parameters.GetNumVolumes() ); outImage->Allocate(); typename OutputImageType::PixelType temp; temp.SetSize(m_Parameters.GetNumVolumes()); temp.Fill(0.0); outImage->FillBuffer(temp); // ADJUST GEOMETRY FOR FURTHER PROCESSING // is input slize size a power of two? unsigned int x=m_Parameters.m_ImageRegion.GetSize(0); unsigned int y=m_Parameters.m_ImageRegion.GetSize(1); ItkDoubleImgType::SizeType pad; pad[0]=x%2; pad[1]=y%2; pad[2]=0; m_Parameters.m_ImageRegion.SetSize(0, x+pad[0]); m_Parameters.m_ImageRegion.SetSize(1, y+pad[1]); if (m_Parameters.m_FrequencyMap.IsNotNull() && (pad[0]>0 || pad[1]>0)) { itk::ConstantPadImageFilter::Pointer zeroPadder = itk::ConstantPadImageFilter::New(); zeroPadder->SetInput(m_Parameters.m_FrequencyMap); zeroPadder->SetConstant(0); zeroPadder->SetPadUpperBound(pad); zeroPadder->Update(); m_Parameters.m_FrequencyMap = zeroPadder->GetOutput(); } if (m_Parameters.m_MaskImage.IsNotNull() && (pad[0]>0 || pad[1]>0)) { itk::ConstantPadImageFilter::Pointer zeroPadder = itk::ConstantPadImageFilter::New(); zeroPadder->SetInput(m_Parameters.m_MaskImage); zeroPadder->SetConstant(0); zeroPadder->SetPadUpperBound(pad); zeroPadder->Update(); m_Parameters.m_MaskImage = zeroPadder->GetOutput(); } // Apply in-plane upsampling for Gibbs ringing artifact double upsampling = 1; if (m_Parameters.m_DoAddGibbsRinging) upsampling = 2; m_UpsampledSpacing = m_Parameters.m_ImageSpacing; m_UpsampledSpacing[0] /= upsampling; m_UpsampledSpacing[1] /= upsampling; m_UpsampledImageRegion = m_Parameters.m_ImageRegion; m_UpsampledImageRegion.SetSize(0, m_Parameters.m_ImageRegion.GetSize()[0]*upsampling); m_UpsampledImageRegion.SetSize(1, m_Parameters.m_ImageRegion.GetSize()[1]*upsampling); m_UpsampledOrigin = m_Parameters.m_ImageOrigin; m_UpsampledOrigin[0] -= m_Parameters.m_ImageSpacing[0]/2; m_UpsampledOrigin[0] += m_UpsampledSpacing[0]/2; m_UpsampledOrigin[1] -= m_Parameters.m_ImageSpacing[1]/2; m_UpsampledOrigin[1] += m_UpsampledSpacing[1]/2; m_UpsampledOrigin[2] -= m_Parameters.m_ImageSpacing[2]/2; m_UpsampledOrigin[2] += m_UpsampledSpacing[2]/2; // generate double images to store the individual compartment signals m_CompartmentImages.clear(); int numFiberCompartments = m_Parameters.m_FiberModelList.size(); int numNonFiberCompartments = m_Parameters.m_NonFiberModelList.size(); for (int i=0; iSetSpacing( m_UpsampledSpacing ); doubleDwi->SetOrigin( m_UpsampledOrigin ); doubleDwi->SetDirection( m_Parameters.m_ImageDirection ); doubleDwi->SetLargestPossibleRegion( m_UpsampledImageRegion ); doubleDwi->SetBufferedRegion( m_UpsampledImageRegion ); doubleDwi->SetRequestedRegion( m_UpsampledImageRegion ); doubleDwi->SetVectorLength( m_Parameters.GetNumVolumes() ); doubleDwi->Allocate(); DoubleDwiType::PixelType pix; pix.SetSize(m_Parameters.GetNumVolumes()); pix.Fill(0.0); doubleDwi->FillBuffer(pix); m_CompartmentImages.push_back(doubleDwi); } // initialize output volume fraction images m_VolumeFractions.clear(); for (int i=0; iSetSpacing( m_UpsampledSpacing ); doubleImg->SetOrigin( m_UpsampledOrigin ); doubleImg->SetDirection( m_Parameters.m_ImageDirection ); doubleImg->SetLargestPossibleRegion( m_UpsampledImageRegion ); doubleImg->SetBufferedRegion( m_UpsampledImageRegion ); doubleImg->SetRequestedRegion( m_UpsampledImageRegion ); doubleImg->Allocate(); doubleImg->FillBuffer(0); m_VolumeFractions.push_back(doubleImg); } // get volume fraction images ItkDoubleImgType::Pointer sumImage = ItkDoubleImgType::New(); bool foundVolumeFractionImage = false; for (int i=0; iGetVolumeFractionImage().IsNotNull()) { foundVolumeFractionImage = true; itk::ConstantPadImageFilter::Pointer zeroPadder = itk::ConstantPadImageFilter::New(); zeroPadder->SetInput(m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()); zeroPadder->SetConstant(0); zeroPadder->SetPadUpperBound(pad); zeroPadder->Update(); m_Parameters.m_NonFiberModelList[i]->SetVolumeFractionImage(zeroPadder->GetOutput()); sumImage->SetSpacing( m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetSpacing() ); sumImage->SetOrigin( m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetOrigin() ); sumImage->SetDirection( m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetDirection() ); sumImage->SetLargestPossibleRegion( m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetLargestPossibleRegion() ); sumImage->SetBufferedRegion( m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetLargestPossibleRegion() ); sumImage->SetRequestedRegion( m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetLargestPossibleRegion() ); sumImage->Allocate(); sumImage->FillBuffer(0); break; } } if (!foundVolumeFractionImage) { sumImage->SetSpacing( m_UpsampledSpacing ); sumImage->SetOrigin( m_UpsampledOrigin ); sumImage->SetDirection( m_Parameters.m_ImageDirection ); sumImage->SetLargestPossibleRegion( m_UpsampledImageRegion ); sumImage->SetBufferedRegion( m_UpsampledImageRegion ); sumImage->SetRequestedRegion( m_UpsampledImageRegion ); sumImage->Allocate(); sumImage->FillBuffer(0.0); } for (int i=0; iGetVolumeFractionImage().IsNull()) { ItkDoubleImgType::Pointer doubleImg = ItkDoubleImgType::New(); doubleImg->SetSpacing( sumImage->GetSpacing() ); doubleImg->SetOrigin( sumImage->GetOrigin() ); doubleImg->SetDirection( sumImage->GetDirection() ); doubleImg->SetLargestPossibleRegion( sumImage->GetLargestPossibleRegion() ); doubleImg->SetBufferedRegion( sumImage->GetLargestPossibleRegion() ); doubleImg->SetRequestedRegion( sumImage->GetLargestPossibleRegion() ); doubleImg->Allocate(); doubleImg->FillBuffer(1.0/numNonFiberCompartments); m_Parameters.m_NonFiberModelList[i]->SetVolumeFractionImage(doubleImg); } ImageRegionIterator it(m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage(), m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetLargestPossibleRegion()); while(!it.IsAtEnd()) { sumImage->SetPixel(it.GetIndex(), sumImage->GetPixel(it.GetIndex())+it.Get()); ++it; } } for (int i=0; i it(m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage(), m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetLargestPossibleRegion()); while(!it.IsAtEnd()) { if (sumImage->GetPixel(it.GetIndex())>0) it.Set(it.Get()/sumImage->GetPixel(it.GetIndex())); ++it; } } // resample mask image and frequency map to fit upsampled geometry if (m_Parameters.m_DoAddGibbsRinging) { if (m_Parameters.m_MaskImage.IsNotNull()) { // rescale mask image (otherwise there are problems with the resampling) itk::RescaleIntensityImageFilter::Pointer rescaler = itk::RescaleIntensityImageFilter::New(); rescaler->SetInput(0,m_Parameters.m_MaskImage); rescaler->SetOutputMaximum(100); rescaler->SetOutputMinimum(0); rescaler->Update(); // resample mask image itk::ResampleImageFilter::Pointer resampler = itk::ResampleImageFilter::New(); resampler->SetInput(rescaler->GetOutput()); resampler->SetOutputParametersFromImage(m_Parameters.m_MaskImage); resampler->SetSize(m_UpsampledImageRegion.GetSize()); resampler->SetOutputSpacing(m_UpsampledSpacing); resampler->SetOutputOrigin(m_UpsampledOrigin); itk::NearestNeighborInterpolateImageFunction::Pointer nn_interpolator = itk::NearestNeighborInterpolateImageFunction::New(); resampler->SetInterpolator(nn_interpolator); resampler->Update(); m_Parameters.m_MaskImage = resampler->GetOutput(); itk::ImageFileWriter::Pointer w = itk::ImageFileWriter::New(); w->SetFileName("/local/mask_ups.nrrd"); w->SetInput(m_Parameters.m_MaskImage); w->Update(); } // resample frequency map if (m_Parameters.m_FrequencyMap.IsNotNull()) { itk::ResampleImageFilter::Pointer resampler = itk::ResampleImageFilter::New(); resampler->SetInput(m_Parameters.m_FrequencyMap); resampler->SetOutputParametersFromImage(m_Parameters.m_FrequencyMap); resampler->SetSize(m_UpsampledImageRegion.GetSize()); resampler->SetOutputSpacing(m_UpsampledSpacing); resampler->SetOutputOrigin(m_UpsampledOrigin); itk::NearestNeighborInterpolateImageFunction::Pointer nn_interpolator = itk::NearestNeighborInterpolateImageFunction::New(); resampler->SetInterpolator(nn_interpolator); resampler->Update(); m_Parameters.m_FrequencyMap = resampler->GetOutput(); } } // no input tissue mask is set -> create default bool maskImageSet = true; if (m_Parameters.m_MaskImage.IsNull()) { m_StatusText += "No tissue mask set\n"; MITK_INFO << "No tissue mask set"; m_Parameters.m_MaskImage = ItkUcharImgType::New(); m_Parameters.m_MaskImage->SetSpacing( m_UpsampledSpacing ); m_Parameters.m_MaskImage->SetOrigin( m_UpsampledOrigin ); m_Parameters.m_MaskImage->SetDirection( m_Parameters.m_ImageDirection ); m_Parameters.m_MaskImage->SetLargestPossibleRegion( m_UpsampledImageRegion ); m_Parameters.m_MaskImage->SetBufferedRegion( m_UpsampledImageRegion ); m_Parameters.m_MaskImage->SetRequestedRegion( m_UpsampledImageRegion ); m_Parameters.m_MaskImage->Allocate(); m_Parameters.m_MaskImage->FillBuffer(1); maskImageSet = false; } else { m_StatusText += "Using tissue mask\n"; MITK_INFO << "Using tissue mask"; } m_Parameters.m_ImageRegion = croppedRegion; x=m_Parameters.m_ImageRegion.GetSize(0); y=m_Parameters.m_ImageRegion.GetSize(1); if ( x%2 == 1 ) m_Parameters.m_ImageRegion.SetSize(0, x+1); if ( y%2 == 1 ) m_Parameters.m_ImageRegion.SetSize(1, y+1); // resample fiber bundle for sufficient voxel coverage m_StatusText += "\n"+this->GetTime()+" > Resampling fibers ...\n"; double segmentVolume = 0.0001; float minSpacing = 1; if(m_UpsampledSpacing[0]GetDeepCopy(); double volumeAccuracy = 10; fiberBundle->ResampleFibers(minSpacing/volumeAccuracy); double mmRadius = m_Parameters.m_AxonRadius/1000; if (mmRadius>0) segmentVolume = M_PI*mmRadius*mmRadius*minSpacing/volumeAccuracy; double maxVolume = 0; double voxelVolume = m_UpsampledSpacing[0]*m_UpsampledSpacing[1]*m_UpsampledSpacing[2]; ofstream logFile; if (m_Parameters.m_DoAddMotion) { std::string fileName = "fiberfox_motion_0.log"; std::string filePath = mitk::IOUtil::GetTempPath(); if (m_Parameters.m_OutputPath.size()>0) filePath = m_Parameters.m_OutputPath; int c = 1; while (itksys::SystemTools::FileExists((filePath+fileName).c_str())) { fileName = "fiberfox_motion_"; fileName += boost::lexical_cast(c); fileName += ".log"; c++; } logFile.open((filePath+fileName).c_str()); logFile << "0 rotation: 0,0,0; translation: 0,0,0\n"; if (m_Parameters.m_DoRandomizeMotion) { m_StatusText += "Adding random motion artifacts:\n"; m_StatusText += "Maximum rotation: +/-" + boost::lexical_cast(m_Parameters.m_Rotation) + "°\n"; m_StatusText += "Maximum translation: +/-" + boost::lexical_cast(m_Parameters.m_Translation) + "mm\n"; } else { m_StatusText += "Adding linear motion artifacts:\n"; m_StatusText += "Maximum rotation: " + boost::lexical_cast(m_Parameters.m_Rotation) + "°\n"; m_StatusText += "Maximum translation: " + boost::lexical_cast(m_Parameters.m_Translation) + "mm\n"; } m_StatusText += "Motion logfile: " + (filePath+fileName) + "\n"; MITK_INFO << "Adding motion artifacts"; MITK_INFO << "Maximum rotation: " << m_Parameters.m_Rotation; MITK_INFO << "Maxmimum translation: " << m_Parameters.m_Translation; } maxVolume = 0; m_StatusText += "\n"+this->GetTime()+" > Generating " + boost::lexical_cast(numFiberCompartments+numNonFiberCompartments) + "-compartment diffusion-weighted signal.\n"; int numFibers = m_FiberBundle->GetNumFibers(); boost::progress_display disp(numFibers*m_Parameters.GetNumVolumes()); // get transform for motion artifacts FiberBundleType fiberBundleTransformed = fiberBundle; DoubleVectorType rotation = m_Parameters.m_Rotation/m_Parameters.GetNumVolumes(); DoubleVectorType translation = m_Parameters.m_Translation/m_Parameters.GetNumVolumes(); // creat image to hold transformed mask (motion artifact) ItkUcharImgType::Pointer tempTissueMask = ItkUcharImgType::New(); itk::ImageDuplicator::Pointer duplicator = itk::ImageDuplicator::New(); duplicator->SetInputImage(m_Parameters.m_MaskImage); duplicator->Update(); tempTissueMask = duplicator->GetOutput(); // second upsampling needed for motion artifacts ImageRegion<3> upsampledImageRegion = m_UpsampledImageRegion; DoubleVectorType upsampledSpacing = m_UpsampledSpacing; upsampledSpacing[0] /= 4; upsampledSpacing[1] /= 4; upsampledSpacing[2] /= 4; upsampledImageRegion.SetSize(0, m_UpsampledImageRegion.GetSize()[0]*4); upsampledImageRegion.SetSize(1, m_UpsampledImageRegion.GetSize()[1]*4); upsampledImageRegion.SetSize(2, m_UpsampledImageRegion.GetSize()[2]*4); itk::Point upsampledOrigin = m_UpsampledOrigin; upsampledOrigin[0] -= m_UpsampledSpacing[0]/2; upsampledOrigin[0] += upsampledSpacing[0]/2; upsampledOrigin[1] -= m_UpsampledSpacing[1]/2; upsampledOrigin[1] += upsampledSpacing[1]/2; upsampledOrigin[2] -= m_UpsampledSpacing[2]/2; upsampledOrigin[2] += upsampledSpacing[2]/2; ItkUcharImgType::Pointer upsampledTissueMask = ItkUcharImgType::New(); itk::ResampleImageFilter::Pointer upsampler = itk::ResampleImageFilter::New(); upsampler->SetInput(m_Parameters.m_MaskImage); upsampler->SetOutputParametersFromImage(m_Parameters.m_MaskImage); upsampler->SetSize(upsampledImageRegion.GetSize()); upsampler->SetOutputSpacing(upsampledSpacing); upsampler->SetOutputOrigin(upsampledOrigin); itk::NearestNeighborInterpolateImageFunction::Pointer nn_interpolator = itk::NearestNeighborInterpolateImageFunction::New(); upsampler->SetInterpolator(nn_interpolator); upsampler->Update(); upsampledTissueMask = upsampler->GetOutput(); unsigned long lastTick = 0; switch (m_Parameters.m_DiffusionDirectionMode) { case(FiberfoxParameters<>::FIBER_TANGENT_DIRECTIONS): { m_StatusText += "0% 10 20 30 40 50 60 70 80 90 100%\n"; m_StatusText += "|----|----|----|----|----|----|----|----|----|----|\n*"; for (unsigned int g=0; gSetSpacing( m_UpsampledSpacing ); intraAxonalVolumeImage->SetOrigin( m_UpsampledOrigin ); intraAxonalVolumeImage->SetDirection( m_Parameters.m_ImageDirection ); intraAxonalVolumeImage->SetLargestPossibleRegion( m_UpsampledImageRegion ); intraAxonalVolumeImage->SetBufferedRegion( m_UpsampledImageRegion ); intraAxonalVolumeImage->SetRequestedRegion( m_UpsampledImageRegion ); intraAxonalVolumeImage->Allocate(); intraAxonalVolumeImage->FillBuffer(0); vtkPolyData* fiberPolyData = fiberBundleTransformed->GetFiberPolyData(); // generate fiber signal (if there are any fiber models present) if (!m_Parameters.m_FiberModelList.empty()) for( int i=0; iGetCell(i); int numPoints = cell->GetNumberOfPoints(); vtkPoints* points = cell->GetPoints(); if (numPoints<2) continue; for( int j=0; jGetAbortGenerateData()) { m_StatusText += "\n"+this->GetTime()+" > Simulation aborted\n"; return; } double* temp = points->GetPoint(j); itk::Point vertex = GetItkPoint(temp); itk::Vector v = GetItkVector(temp); itk::Vector dir(3); if (jGetPoint(j+1))-v; else dir = v-GetItkVector(points->GetPoint(j-1)); if (dir.GetSquaredNorm()<0.0001 || dir[0]!=dir[0] || dir[1]!=dir[1] || dir[2]!=dir[2]) continue; itk::Index<3> idx; itk::ContinuousIndex contIndex; tempTissueMask->TransformPhysicalPointToIndex(vertex, idx); tempTissueMask->TransformPhysicalPointToContinuousIndex(vertex, contIndex); if (!tempTissueMask->GetLargestPossibleRegion().IsInside(idx) || tempTissueMask->GetPixel(idx)<=0) continue; // generate signal for each fiber compartment for (int k=0; kSetFiberDirection(dir); DoubleDwiType::PixelType pix = m_CompartmentImages.at(k)->GetPixel(idx); pix[g] += segmentVolume*m_Parameters.m_FiberModelList[k]->SimulateMeasurement(g); m_CompartmentImages.at(k)->SetPixel(idx, pix); } // update fiber volume image double vol = intraAxonalVolumeImage->GetPixel(idx) + segmentVolume; intraAxonalVolumeImage->SetPixel(idx, vol); if (g==0 && vol>maxVolume) maxVolume = vol; } // progress report ++disp; unsigned long newTick = 50*disp.count()/disp.expected_count(); for (unsigned int tick = 0; tick<(newTick-lastTick); tick++) m_StatusText += "*"; lastTick = newTick; } // generate non-fiber signal ImageRegionIterator it3(tempTissueMask, tempTissueMask->GetLargestPossibleRegion()); double fact = 1; if (m_Parameters.m_AxonRadius<0.0001 || maxVolume>voxelVolume) fact = voxelVolume/maxVolume; while(!it3.IsAtEnd()) { if (it3.Get()>0) { DoubleDwiType::IndexType index = it3.GetIndex(); // get fiber volume fraction double intraAxonalVolume = intraAxonalVolumeImage->GetPixel(index)*fact; for (int i=0; iGetPixel(index); pix[g] *= fact; m_CompartmentImages.at(i)->SetPixel(index, pix); } if (intraAxonalVolume>0.0001 && m_Parameters.m_DoDisablePartialVolume) // only fiber in voxel { DoubleDwiType::PixelType pix = m_CompartmentImages.at(0)->GetPixel(index); pix[g] *= voxelVolume/intraAxonalVolume; m_CompartmentImages.at(0)->SetPixel(index, pix); m_VolumeFractions.at(0)->SetPixel(index, 1); for (int i=1; iGetPixel(index); pix[g] = 0; m_CompartmentImages.at(i)->SetPixel(index, pix); } } else { m_VolumeFractions.at(0)->SetPixel(index, intraAxonalVolume/voxelVolume); itk::Point point; tempTissueMask->TransformIndexToPhysicalPoint(index, point); if (m_Parameters.m_DoAddMotion) { if (m_Parameters.m_DoRandomizeMotion && g>0) point = fiberBundle->TransformPoint(point.GetVnlVector(), -rotation[0],-rotation[1],-rotation[2],-translation[0],-translation[1],-translation[2]); else point = fiberBundle->TransformPoint(point.GetVnlVector(), -rotation[0]*g,-rotation[1]*g,-rotation[2]*g,-translation[0]*g,-translation[1]*g,-translation[2]*g); } if (m_Parameters.m_DoDisablePartialVolume) { int maxVolumeIndex = 0; double maxWeight = 0; for (int i=0; i1) { DoubleDwiType::IndexType newIndex; m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->TransformPhysicalPointToIndex(point, newIndex); if (!m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetLargestPossibleRegion().IsInside(newIndex)) continue; weight = m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetPixel(newIndex); } if (weight>maxWeight) { maxWeight = weight; maxVolumeIndex = i; } } DoubleDwiType::Pointer doubleDwi = m_CompartmentImages.at(maxVolumeIndex+numFiberCompartments); DoubleDwiType::PixelType pix = doubleDwi->GetPixel(index); pix[g] += m_Parameters.m_NonFiberModelList[maxVolumeIndex]->SimulateMeasurement(g); doubleDwi->SetPixel(index, pix); m_VolumeFractions.at(maxVolumeIndex+numFiberCompartments)->SetPixel(index, 1); } else { double extraAxonalVolume = voxelVolume-intraAxonalVolume; // non-fiber volume double interAxonalVolume = 0; if (numFiberCompartments>1) interAxonalVolume = extraAxonalVolume * intraAxonalVolume/voxelVolume; // inter-axonal fraction of non fiber compartment scales linearly with f double other = extraAxonalVolume - interAxonalVolume; // rest of compartment double singleinter = interAxonalVolume/(numFiberCompartments-1); // adjust non-fiber and intra-axonal signal for (int i=1; iGetPixel(index); if (intraAxonalVolume>0) // remove scaling by intra-axonal volume from inter-axonal compartment pix[g] /= intraAxonalVolume; pix[g] *= singleinter; m_CompartmentImages.at(i)->SetPixel(index, pix); m_VolumeFractions.at(i)->SetPixel(index, singleinter/voxelVolume); } for (int i=0; i1) { DoubleDwiType::IndexType newIndex; m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->TransformPhysicalPointToIndex(point, newIndex); if (!m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetLargestPossibleRegion().IsInside(newIndex)) continue; weight = m_Parameters.m_NonFiberModelList[i]->GetVolumeFractionImage()->GetPixel(newIndex); } DoubleDwiType::Pointer doubleDwi = m_CompartmentImages.at(i+numFiberCompartments); DoubleDwiType::PixelType pix = doubleDwi->GetPixel(index); pix[g] += m_Parameters.m_NonFiberModelList[i]->SimulateMeasurement(g)*other*weight; doubleDwi->SetPixel(index, pix); m_VolumeFractions.at(i+numFiberCompartments)->SetPixel(index, other/voxelVolume*weight); } } } } ++it3; } // move fibers if (m_Parameters.m_DoAddMotion && gGetDeepCopy(); rotation[0] = m_RandGen->GetVariateWithClosedRange(m_Parameters.m_Rotation[0]*2)-m_Parameters.m_Rotation[0]; rotation[1] = m_RandGen->GetVariateWithClosedRange(m_Parameters.m_Rotation[1]*2)-m_Parameters.m_Rotation[1]; rotation[2] = m_RandGen->GetVariateWithClosedRange(m_Parameters.m_Rotation[2]*2)-m_Parameters.m_Rotation[2]; translation[0] = m_RandGen->GetVariateWithClosedRange(m_Parameters.m_Translation[0]*2)-m_Parameters.m_Translation[0]; translation[1] = m_RandGen->GetVariateWithClosedRange(m_Parameters.m_Translation[1]*2)-m_Parameters.m_Translation[1]; translation[2] = m_RandGen->GetVariateWithClosedRange(m_Parameters.m_Translation[2]*2)-m_Parameters.m_Translation[2]; } // rotate mask image if (maskImageSet) { ImageRegionIterator maskIt(upsampledTissueMask, upsampledTissueMask->GetLargestPossibleRegion()); tempTissueMask->FillBuffer(0); while(!maskIt.IsAtEnd()) { if (maskIt.Get()<=0) { ++maskIt; continue; } DoubleDwiType::IndexType index = maskIt.GetIndex(); itk::Point point; upsampledTissueMask->TransformIndexToPhysicalPoint(index, point); if (m_Parameters.m_DoRandomizeMotion) point = fiberBundle->TransformPoint(point.GetVnlVector(), rotation[0],rotation[1],rotation[2],translation[0],translation[1],translation[2]); else point = fiberBundle->TransformPoint(point.GetVnlVector(), rotation[0]*(g+1),rotation[1]*(g+1),rotation[2]*(g+1),translation[0]*(g+1),translation[1]*(g+1),translation[2]*(g+1)); tempTissueMask->TransformPhysicalPointToIndex(point, index); if (tempTissueMask->GetLargestPossibleRegion().IsInside(index)) tempTissueMask->SetPixel(index,100); ++maskIt; } } // rotate fibers if (logFile.is_open()) { logFile << g+1 << " rotation: " << rotation[0] << "," << rotation[1] << "," << rotation[2] << ";"; logFile << " translation: " << translation[0] << "," << translation[1] << "," << translation[2] << "\n"; } fiberBundleTransformed->TransformFibers(rotation[0],rotation[1],rotation[2],translation[0],translation[1],translation[2]); } } break; } case (FiberfoxParameters<>::MAIN_FIBER_DIRECTIONS): { typedef itk::Image< itk::Vector< float, 3>, 3 > ItkDirectionImage3DType; typedef itk::VectorContainer< unsigned int, ItkDirectionImage3DType::Pointer > ItkDirectionImageContainerType; itk::TractsToVectorImageFilter::Pointer fOdfFilter = itk::TractsToVectorImageFilter::New(); fOdfFilter->SetFiberBundle(fiberBundle); fOdfFilter->SetMaskImage(tempTissueMask); fOdfFilter->SetAngularThreshold(cos(45*M_PI/180)); fOdfFilter->SetNormalizeVectors(false); fOdfFilter->SetUseWorkingCopy(false); fOdfFilter->SetSizeThreshold(0); fOdfFilter->SetMaxNumDirections(3); fOdfFilter->Update(); ItkDirectionImageContainerType::Pointer directionImageContainer = fOdfFilter->GetDirectionImageContainer(); { ItkUcharImgType::Pointer numDirImage = fOdfFilter->GetNumDirectionsImage(); typedef itk::ImageFileWriter< ItkUcharImgType > WriterType; WriterType::Pointer writer = WriterType::New(); writer->SetFileName("/local/NumDirections.nrrd"); writer->SetInput(numDirImage); writer->Update(); } ItkDoubleImgType::Pointer intraAxonalVolumeImage = ItkDoubleImgType::New(); intraAxonalVolumeImage->SetSpacing( m_UpsampledSpacing ); intraAxonalVolumeImage->SetOrigin( m_UpsampledOrigin ); intraAxonalVolumeImage->SetDirection( m_Parameters.m_ImageDirection ); intraAxonalVolumeImage->SetLargestPossibleRegion( m_UpsampledImageRegion ); intraAxonalVolumeImage->SetBufferedRegion( m_UpsampledImageRegion ); intraAxonalVolumeImage->SetRequestedRegion( m_UpsampledImageRegion ); intraAxonalVolumeImage->Allocate(); intraAxonalVolumeImage->FillBuffer(0); itk::TractDensityImageFilter< ItkDoubleImgType >::Pointer generator = itk::TractDensityImageFilter< ItkDoubleImgType >::New(); generator->SetFiberBundle(fiberBundle); generator->SetBinaryOutput(false); generator->SetOutputAbsoluteValues(false); generator->SetInputImage(intraAxonalVolumeImage); generator->SetUseImageGeometry(true); generator->Update(); intraAxonalVolumeImage = generator->GetOutput(); m_StatusText += "0% 10 20 30 40 50 60 70 80 90 100%\n"; m_StatusText += "|----|----|----|----|----|----|----|----|----|----|\n*"; boost::progress_display disp(tempTissueMask->GetLargestPossibleRegion().GetNumberOfPixels()); ImageRegionIterator< ItkUcharImgType > it(tempTissueMask, tempTissueMask->GetLargestPossibleRegion()); while(!it.IsAtEnd()) { ++disp; unsigned long newTick = 50*disp.count()/disp.expected_count(); for (unsigned int tick = 0; tick<(newTick-lastTick); tick++) m_StatusText += "*"; lastTick = newTick; if (this->GetAbortGenerateData()) { m_StatusText += "\n"+this->GetTime()+" > Simulation aborted\n"; return; } if (it.Get()>0) { int count = 0; DoubleDwiType::PixelType pix = m_CompartmentImages.at(0)->GetPixel(it.GetIndex()); for (unsigned int i=0; iSize(); i++) { - itk::Vector< float, 3> dir = directionImageContainer->GetElement(i)->GetPixel(it.GetIndex()); + itk::Vector< double, 3> dir; + dir.CastFrom(directionImageContainer->GetElement(i)->GetPixel(it.GetIndex())); double norm = dir.GetNorm(); if (norm>0.0001) { int modelIndex = m_RandGen->GetIntegerVariate(m_Parameters.m_FiberModelList.size()-1); m_Parameters.m_FiberModelList.at(modelIndex)->SetFiberDirection(dir); pix += m_Parameters.m_FiberModelList.at(modelIndex)->SimulateMeasurement()*norm; count++; } } if (count>0) pix /= count; pix *= intraAxonalVolumeImage->GetPixel(it.GetIndex()); // GM/CSF { int modelIndex = m_RandGen->GetIntegerVariate(m_Parameters.m_NonFiberModelList.size()-1); pix += (1-intraAxonalVolumeImage->GetPixel(it.GetIndex()))*m_Parameters.m_NonFiberModelList.at(modelIndex)->SimulateMeasurement(); } m_CompartmentImages.at(0)->SetPixel(it.GetIndex(), pix); } ++it; } break; } case (FiberfoxParameters<>::RANDOM_DIRECTIONS): { ItkUcharImgType::Pointer numDirectionsImage = ItkUcharImgType::New(); numDirectionsImage->SetSpacing( m_UpsampledSpacing ); numDirectionsImage->SetOrigin( m_UpsampledOrigin ); numDirectionsImage->SetDirection( m_Parameters.m_ImageDirection ); numDirectionsImage->SetLargestPossibleRegion( m_UpsampledImageRegion ); numDirectionsImage->SetBufferedRegion( m_UpsampledImageRegion ); numDirectionsImage->SetRequestedRegion( m_UpsampledImageRegion ); numDirectionsImage->Allocate(); numDirectionsImage->FillBuffer(0); m_StatusText += "0% 10 20 30 40 50 60 70 80 90 100%\n"; m_StatusText += "|----|----|----|----|----|----|----|----|----|----|\n*"; boost::progress_display disp(tempTissueMask->GetLargestPossibleRegion().GetNumberOfPixels()); ImageRegionIterator it(tempTissueMask, tempTissueMask->GetLargestPossibleRegion()); while(!it.IsAtEnd()) { ++disp; unsigned long newTick = 50*disp.count()/disp.expected_count(); for (unsigned int tick = 0; tick<(newTick-lastTick); tick++) m_StatusText += "*"; lastTick = newTick; if (this->GetAbortGenerateData()) { m_StatusText += "\n"+this->GetTime()+" > Simulation aborted\n"; return; } if (it.Get()>0) { int numFibs = m_RandGen->GetIntegerVariate(2)+1; DoubleDwiType::PixelType pix = m_CompartmentImages.at(0)->GetPixel(it.GetIndex()); double volume = m_RandGen->GetVariateWithClosedRange(0.3); double sum = 0; std::vector< double > fractions; for (int i=0; iGetVariateWithClosedRange(0.5)); sum += fractions.at(i); } for (int i=0; i > directions; for (int i=0; iGetVariateWithClosedRange(2)-1.0; fib[1] = m_RandGen->GetVariateWithClosedRange(2)-1.0; fib[2] = m_RandGen->GetVariateWithClosedRange(2)-1.0; fib.Normalize(); double min = 0; for (unsigned int d=0; dmin) min = angle; } if (min<0.5) { m_Parameters.m_FiberModelList.at(0)->SetFiberDirection(fib); pix += m_Parameters.m_FiberModelList.at(0)->SimulateMeasurement()*fractions[i]; directions.push_back(fib); } else i--; } pix *= (1-volume); // CSF/GM { // int modelIndex = m_RandGen->GetIntegerVariate(m_Parameters.m_NonFiberModelList.size()-1); pix += volume*m_Parameters.m_NonFiberModelList.at(0)->SimulateMeasurement(); } m_CompartmentImages.at(0)->SetPixel(it.GetIndex(), pix); numDirectionsImage->SetPixel(it.GetIndex(), numFibs); } ++it; } itk::ImageFileWriter< ItkUcharImgType >::Pointer wr = itk::ImageFileWriter< ItkUcharImgType >::New(); wr->SetInput(numDirectionsImage); wr->SetFileName("/local/NumDirections.nrrd"); wr->Update(); } } if (logFile.is_open()) { logFile << "DONE"; logFile.close(); } m_StatusText += "\n\n"; if (this->GetAbortGenerateData()) { m_StatusText += "\n"+this->GetTime()+" > Simulation aborted\n"; return; } // do k-space stuff DoubleDwiType::Pointer doubleOutImage; if ( m_Parameters.m_SimulateKspaceAcquisition ) { m_StatusText += this->GetTime()+" > Adjusting complex signal\n"; MITK_INFO << "Adjusting complex signal:"; if (m_Parameters.m_DoSimulateRelaxation) m_StatusText += "Simulating signal relaxation\n"; if (m_Parameters.m_FrequencyMap.IsNotNull()) m_StatusText += "Simulating distortions\n"; if (m_Parameters.m_DoAddGibbsRinging) m_StatusText += "Simulating ringing artifacts\n"; if (m_Parameters.m_EddyStrength>0) m_StatusText += "Simulating eddy currents\n"; if (m_Parameters.m_Spikes>0) m_StatusText += "Simulating spikes\n"; if (m_Parameters.m_CroppingFactor<1.0) m_StatusText += "Simulating aliasing artifacts\n"; if (m_Parameters.m_KspaceLineOffset>0) m_StatusText += "Simulating ghosts\n"; doubleOutImage = DoKspaceStuff(m_CompartmentImages); m_Parameters.m_SignalScale = 1; // already scaled in DoKspaceStuff } else { m_StatusText += this->GetTime()+" > Summing compartments\n"; MITK_INFO << "Summing compartments"; doubleOutImage = m_CompartmentImages.at(0); for (unsigned int i=1; i::Pointer adder = itk::AddImageFilter< DoubleDwiType, DoubleDwiType, DoubleDwiType>::New(); adder->SetInput1(doubleOutImage); adder->SetInput2(m_CompartmentImages.at(i)); adder->Update(); doubleOutImage = adder->GetOutput(); } } if (this->GetAbortGenerateData()) { m_StatusText += "\n"+this->GetTime()+" > Simulation aborted\n"; return; } m_StatusText += this->GetTime()+" > Finalizing image\n"; MITK_INFO << "Finalizing image"; if (m_Parameters.m_SignalScale>1) m_StatusText += " Scaling signal\n"; if (m_Parameters.m_NoiseModel!=NULL) m_StatusText += " Adding noise\n"; unsigned int window = 0; unsigned int min = itk::NumericTraits::max(); ImageRegionIterator it4 (outImage, outImage->GetLargestPossibleRegion()); DoubleDwiType::PixelType signal; signal.SetSize(m_Parameters.GetNumVolumes()); boost::progress_display disp2(outImage->GetLargestPossibleRegion().GetNumberOfPixels()); m_StatusText += "0% 10 20 30 40 50 60 70 80 90 100%\n"; m_StatusText += "|----|----|----|----|----|----|----|----|----|----|\n*"; lastTick = 0; while(!it4.IsAtEnd()) { if (this->GetAbortGenerateData()) { m_StatusText += "\n"+this->GetTime()+" > Simulation aborted\n"; return; } ++disp2; unsigned long newTick = 50*disp2.count()/disp2.expected_count(); for (unsigned long tick = 0; tick<(newTick-lastTick); tick++) m_StatusText += "*"; lastTick = newTick; typename OutputImageType::IndexType index = it4.GetIndex(); signal = doubleOutImage->GetPixel(index)*m_Parameters.m_SignalScale; if (m_Parameters.m_NoiseModel!=NULL) m_Parameters.m_NoiseModel->AddNoise(signal); for (unsigned int i=0; i0) signal[i] = floor(signal[i]+0.5); else signal[i] = ceil(signal[i]-0.5); if ( (!m_Parameters.IsBaselineIndex(i) || signal.Size()==1) && signal[i]>window) window = signal[i]; if ( (!m_Parameters.IsBaselineIndex(i) || signal.Size()==1) && signal[i]SetNthOutput(0, outImage); m_StatusText += "\n\n"; m_StatusText += "Finished simulation\n"; m_StatusText += "Simulation time: "+GetTime(); m_TimeProbe.Stop(); } template< class PixelType > itk::Point TractsToDWIImageFilter< PixelType >::GetItkPoint(double point[3]) { itk::Point itkPoint; itkPoint[0] = point[0]; itkPoint[1] = point[1]; itkPoint[2] = point[2]; return itkPoint; } template< class PixelType > itk::Vector TractsToDWIImageFilter< PixelType >::GetItkVector(double point[3]) { itk::Vector itkVector; itkVector[0] = point[0]; itkVector[1] = point[1]; itkVector[2] = point[2]; return itkVector; } template< class PixelType > vnl_vector_fixed TractsToDWIImageFilter< PixelType >::GetVnlVector(double point[3]) { vnl_vector_fixed vnlVector; vnlVector[0] = point[0]; vnlVector[1] = point[1]; vnlVector[2] = point[2]; return vnlVector; } template< class PixelType > vnl_vector_fixed TractsToDWIImageFilter< PixelType >::GetVnlVector(Vector& vector) { vnl_vector_fixed vnlVector; vnlVector[0] = vector[0]; vnlVector[1] = vector[1]; vnlVector[2] = vector[2]; return vnlVector; } template< class PixelType > double TractsToDWIImageFilter< PixelType >::RoundToNearest(double num) { return (num > 0.0) ? floor(num + 0.5) : ceil(num - 0.5); } template< class PixelType > std::string TractsToDWIImageFilter< PixelType >::GetTime() { m_TimeProbe.Stop(); unsigned long total = RoundToNearest(m_TimeProbe.GetTotal()); unsigned long hours = total/3600; unsigned long minutes = (total%3600)/60; unsigned long seconds = total%60; std::string out = ""; out.append(boost::lexical_cast(hours)); out.append(":"); out.append(boost::lexical_cast(minutes)); out.append(":"); out.append(boost::lexical_cast(seconds)); m_TimeProbe.Start(); return out; } } diff --git a/Plugins/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkPreprocessingViewControls.ui b/Plugins/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkPreprocessingViewControls.ui index 393f8ac3eb..b2460f04b2 100644 --- a/Plugins/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkPreprocessingViewControls.ui +++ b/Plugins/org.mitk.gui.qt.diffusionimaging/src/internal/QmitkPreprocessingViewControls.ui @@ -1,1574 +1,1574 @@ QmitkPreprocessingViewControls 0 0 639 1148 0 0 false QmitkPreprocessingViewControls true Please Select Input Data Image: <html><head/><body><p><span style=" color:#ff0000;">mandatory</span></p></body></html> true 0 Gradients Qt::Vertical 20 40 QFrame::NoFrame QFrame::Raised 0 0 0 0 6 false Sometimes the gradient directions are not located on one half sphere. Mirror gradients to half sphere false Round b-values false Retain only the specified number of gradient directions and according image volumes. The retained directions are spread equally over the half sphere using an iterative energy repulsion strategy. Reduce number of gradients <html><head/><body><p>Define the sampling frame the b-Values are rounded with.</p></body></html> Sampling frame: false <html><head/><body><p>Round b-values to nearest multiple of this value (click &quot;Round b-value&quot; to create new image with these values).</p></body></html> QAbstractSpinBox::CorrectToNearestValue 1 10000 10 false Generate pointset displaying the gradient vectors (applied measurement frame). Show gradients 0 0 Qt::ScrollBarAsNeeded Qt::ScrollBarAlwaysOff true 100 true false true b-Value Number of gradients Qt::Horizontal 40 20 Image Values Qt::Vertical 20 40 QFrame::NoFrame QFrame::Raised 0 0 0 0 0 QFrame::NoFrame QFrame::Raised 0 0 0 0 Accumulates the information that was acquired with multiple repetitions for one gradient. Vectors do not have to be precisely equal in order to be merged, if a "Merge radius" > 0 is configured. Accumulates the information that was acquired with multiple repetitions for one gradient. Vectors do not have to be precisely equal in order to be merged, if a "Merge radius" > 0 is configured. Accumulates the information that was acquired with multiple repetitions for one gradient. Vectors do not have to be precisely equal in order to be merged, if a "Merge radius" > 0 is configured. 6 2.000000000000000 0.000100000000000 0.001000000000000 Accumulates the information that was acquired with multiple repetitions for one gradient. Vectors do not have to be precisely equal in order to be merged, if a "Merge radius" > 0 is configured. Accumulates the information that was acquired with multiple repetitions for one gradient. Vectors do not have to be precisely equal in order to be merged, if a "Merge radius" > 0 is configured. Accumulates the information that was acquired with multiple repetitions for one gradient. Vectors do not have to be precisely equal in order to be merged, if a "Merge radius" > 0 is configured. Merge radius false Merges selected DWIs of same dimension. If several b-values are present, the resulting image will contain multiple b-shells. Merge selected DWIs false - Each image value is normalized with the corresponding baseline signal value. + Normalize image values QFrame::NoFrame QFrame::Raised 0 0 0 0 0 false Target b-value 100000 500 Select projection method. ADC Average AKC Bi-Exponential false Multiple acquistions of one gradient direction can be averaged. Due to rounding errors, similar gradients often differ in the last decimal positions. The Merge radius allows to average them by taking all directions within a certain radius into account. Average repetitions false Project image values onto one b-shell. Project onto shell QFrame::NoFrame QFrame::Raised 0 0 0 0 0 Select binary mask image. Select normalization reference. White matter CSF Voxel-wise baseline Resample image QFrame::NoFrame QFrame::Raised 0 0 0 0 0 0.010000000000000 2.000000000000000 0.010000000000000 2.000000000000000 0.010000000000000 2.000000000000000 Sampling factor New image spacing New image size QFrame::NoFrame QFrame::Raised 0 0 0 0 0 Interpolator: Nearest neighbour Linear B-spline Windowed sinc false Resample image QFrame::NoFrame QFrame::Raised 0 0 0 0 0 1 10000 1 10000 1 10000 Header Qt::Vertical 20 40 Voxel size 0 0 0 4 4 4 0.000000000000000 99.989999999999995 false Set new voxel size Image size 0 0 0 y: Number of pixels to remove on lower image bound. 999999999 Number of pixels to remove on upper image bound. 999999999 Number of pixels to remove on upper image bound. 999999999 Number of pixels to remove on lower image bound. 999999999 x: Number of pixels to remove on lower image bound. 999999999 Number of pixels to remove on upper image bound. 999999999 z: false Crop image Origin 0 0 0 4 -999999999.000000000000000 999999999.000000000000000 4 -999999999.000000000000000 999999999.000000000000000 4 -99999999.000000000000000 999999999.000000000000000 false Set new origin Qt::Horizontal 40 20 Direction matrix 0 9 0 0 false 0 0 0 0 IBeamCursor true Qt::ScrollBarAlwaysOff Qt::ScrollBarAlwaysOff true false false true true 0 false true true New Row New Row New Row New Column New Column New Column false Diffusion encoding gradient directions are rotated accordingly. Apply new direction Qt::Horizontal 40 20 0 0 Measurment frame 0 0 0 Qt::Horizontal 40 20 false 0 0 0 0 IBeamCursor true Qt::ScrollBarAlwaysOff Qt::ScrollBarAlwaysOff true false false true true 0 false true true New Row New Row New Row New Column New Column New Column false Diffusion encoding gradient directions are rotated accordingly. Apply new measurement frame Remove or extract gradient volumes false Generate pointset displaying the gradient vectors (applied measurement frame). Remove false Generate pointset displaying the gradient vectors (applied measurement frame). Extract Other Create a 3D+t data set containing all b0 images as timesteps Disable averaging false If multiple baseline acquisitions are present, the default behaviour is to output an averaged image. Extract baseline image Qt::Vertical 20 40 false If multiple baseline acquisitions are present, the default behaviour is to output an averaged image. Calculate ADC map false If multiple baseline acquisitions are present, the default behaviour is to output an averaged image. Estimate binary brain mask Maximum number of iterations. 10000 10000 QmitkDataStorageComboBox QComboBox
QmitkDataStorageComboBox.h
 m_B_ValueMap_Rounder_SpinBox m_Blur m_targetBValueSpinBox m_ProjectionMethodBox m_ResampleTypeBox m_ResampleDoubleX m_ResampleDoubleY m_ResampleDoubleZ m_ResampleIntX m_ResampleIntY m_ResampleIntZ m_InterpolatorBox m_HeaderSpacingX m_HeaderSpacingY m_HeaderSpacingZ m_HeaderOriginX m_HeaderOriginY m_HeaderOriginZ m_DirectionMatrixTable m_MeasurementFrameTable m_CheckExtractAll m_BrainMaskIterationsBox tabWidget m_B_ValueMap_TableWidget m_CreateLengthCorrectedDwi m_ShowGradientsButton m_MirrorGradientToHalfSphereButton m_ReduceGradientsButton m_ButtonAverageGradients m_ProjectSignalButton m_NormalizeImageValuesButton m_MergeDwisButton m_ResampleImageButton m_ModifySpacingButton m_ModifyOriginButton m_ModifyDirection m_ModifyMeasurementFrame m_ButtonExtractB0 m_CalcAdcButton m_ExtractBrainMask