diff --git a/Modules/PhotoacousticsAlgorithms/source/OpenCLFilter/mitkPhotoacousticOCLBeamformingFilter.cpp b/Modules/PhotoacousticsAlgorithms/source/OpenCLFilter/mitkPhotoacousticOCLBeamformingFilter.cpp index 6da6fbaa9b..575c29b240 100644 --- a/Modules/PhotoacousticsAlgorithms/source/OpenCLFilter/mitkPhotoacousticOCLBeamformingFilter.cpp +++ b/Modules/PhotoacousticsAlgorithms/source/OpenCLFilter/mitkPhotoacousticOCLBeamformingFilter.cpp @@ -1,265 +1,264 @@ /*=================================================================== 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. ===================================================================*/ #if defined(PHOTOACOUSTICS_USE_GPU) || DOXYGEN #include "./OpenCLFilter/mitkPhotoacousticOCLBeamformingFilter.h" #include "usServiceReference.h" mitk::PhotoacousticOCLBeamformingFilter::PhotoacousticOCLBeamformingFilter() : m_PixelCalculation( NULL ), m_InputImage(mitk::Image::New()), m_ApodizationBuffer(nullptr), m_MemoryLocationsBuffer(nullptr), m_DelaysBuffer(nullptr), m_UsedLinesBuffer(nullptr) { this->AddSourceFile("DAS.cl"); this->AddSourceFile("DMAS.cl"); this->AddSourceFile("sDMAS.cl"); this->m_FilterID = "OpenCLBeamformingFilter"; this->Initialize(); unsigned int dim[] = { 128, 2048, 2 }; mitk::Vector3D spacing; spacing[0] = 1; spacing[1] = 1; spacing[2] = 1; m_InputImage->Initialize(mitk::MakeScalarPixelType(), 3, dim); m_InputImage->SetSpacing(spacing); m_ChunkSize[0] = 128; m_ChunkSize[1] = 128; m_ChunkSize[2] = 8; m_UsedLinesCalculation = mitk::OCLUsedLinesCalculation::New(); m_DelayCalculation = mitk::OCLDelayCalculation::New(); } mitk::PhotoacousticOCLBeamformingFilter::~PhotoacousticOCLBeamformingFilter() { if ( this->m_PixelCalculation ) { clReleaseKernel( m_PixelCalculation ); } if (m_ApodizationBuffer) clReleaseMemObject(m_ApodizationBuffer); } void mitk::PhotoacousticOCLBeamformingFilter::Update() { //Check if context & program available if (!this->Initialize()) { us::ServiceReference ref = GetModuleContext()->GetServiceReference(); OclResourceService* resources = GetModuleContext()->GetService(ref); // clean-up also the resources resources->InvalidateStorage(); mitkThrow() <<"Filter is not initialized. Cannot update."; } else{ // Execute this->Execute(); } } void mitk::PhotoacousticOCLBeamformingFilter::UpdateDataBuffers() { /*us::ServiceReference ref = GetModuleContext()->GetServiceReference(); OclResourceService* resources = GetModuleContext()->GetService(ref); cl_ulong globalMemSize = oclGetGlobalMemSize(resources->GetCurrentDevice());*/ //Initialize the Output try { MITK_DEBUG << "Updating Workgroup size for new dimensions"; size_t outputSize = (size_t)m_Conf.ReconstructionLines * (size_t)m_Conf.SamplesPerLine * (size_t)m_Conf.inputDim[2]; m_OutputDim[0] = m_Conf.ReconstructionLines; m_OutputDim[1] = m_Conf.SamplesPerLine; m_OutputDim[2] = m_Conf.inputDim[2]; this->InitExec(this->m_PixelCalculation, m_OutputDim, outputSize, sizeof(float)); } catch (const mitk::Exception& e) { MITK_ERROR << "Caught exception while initializing filter: " << e.what(); return; } if (BeamformingSettings::SettingsChangedOpenCL(m_Conf, m_ConfOld)) { cl_int clErr = 0; MITK_DEBUG << "Updating GPU Buffers for new configuration"; // create the apodisation buffer if (m_Apodisation == nullptr) { MITK_INFO << "No apodisation function set; Beamforming will be done without any apodisation."; m_Apodisation = new float[1]; m_Apodisation[0] = 1; m_ApodArraySize = 1; } us::ServiceReference ref = GetModuleContext()->GetServiceReference(); OclResourceService* resources = GetModuleContext()->GetService(ref); cl_context gpuContext = resources->GetContext(); if (m_ApodizationBuffer) clReleaseMemObject(m_ApodizationBuffer); this->m_ApodizationBuffer = clCreateBuffer(gpuContext, CL_MEM_READ_ONLY | CL_MEM_USE_HOST_PTR, sizeof(float) * m_ApodArraySize, m_Apodisation, &clErr); CHECK_OCL_ERR(clErr); // calculate used lines m_UsedLinesCalculation->SetConfig(m_Conf); m_UsedLinesCalculation->Update(); m_UsedLinesBuffer = m_UsedLinesCalculation->GetGPUOutput()->GetGPUBuffer(); // calculate the Delays - m_DelayCalculation->SetConfig(m_Conf); m_DelayCalculation->SetInputs(m_UsedLinesBuffer); m_DelayCalculation->Update(); m_DelaysBuffer = m_DelayCalculation->GetGPUOutput()->GetGPUBuffer(); m_ConfOld = m_Conf; } } void mitk::PhotoacousticOCLBeamformingFilter::Execute() { cl_int clErr = 0; UpdateDataBuffers(); clErr = clSetKernelArg(this->m_PixelCalculation, 2, sizeof(cl_mem), &(this->m_UsedLinesBuffer)); clErr |= clSetKernelArg(this->m_PixelCalculation, 3, sizeof(cl_mem), &(this->m_DelaysBuffer)); clErr |= clSetKernelArg(this->m_PixelCalculation, 4, sizeof(cl_mem), &(this->m_ApodizationBuffer)); clErr |= clSetKernelArg(this->m_PixelCalculation, 5, sizeof(cl_ushort), &(this->m_ApodArraySize)); clErr |= clSetKernelArg(this->m_PixelCalculation, 6, sizeof(cl_uint), &(this->m_Conf.inputDim[0])); clErr |= clSetKernelArg(this->m_PixelCalculation, 7, sizeof(cl_uint), &(this->m_Conf.inputDim[1])); clErr |= clSetKernelArg(this->m_PixelCalculation, 8, sizeof(cl_uint), &(this->m_Conf.inputDim[2])); clErr |= clSetKernelArg(this->m_PixelCalculation, 9, sizeof(cl_uint), &(this->m_Conf.ReconstructionLines)); clErr |= clSetKernelArg(this->m_PixelCalculation, 10, sizeof(cl_uint), &(this->m_Conf.SamplesPerLine)); // execute the filter on a 3D NDRange if (m_OutputDim[2] == 1 || m_ChunkSize[2] == 1) { if(!this->ExecuteKernelChunksInBatches(m_PixelCalculation, 2, m_ChunkSize, 16, 50)) mitkThrow() << "openCL Error when executing Kernel"; } else { if(!this->ExecuteKernelChunksInBatches(m_PixelCalculation, 3, m_ChunkSize, 16, 50)) mitkThrow() << "openCL Error when executing Kernel"; } // signalize the GPU-side data changed m_Output->Modified( GPU_DATA ); } us::Module *mitk::PhotoacousticOCLBeamformingFilter::GetModule() { return us::GetModuleContext()->GetModule(); } bool mitk::PhotoacousticOCLBeamformingFilter::Initialize() { bool buildErr = true; cl_int clErr = 0; if ( OclFilter::Initialize() ) { switch (m_Conf.Algorithm) { case BeamformingSettings::BeamformingAlgorithm::DAS: { this->m_PixelCalculation = clCreateKernel(this->m_ClProgram, "ckDAS", &clErr); break; } case BeamformingSettings::BeamformingAlgorithm::DMAS: { this->m_PixelCalculation = clCreateKernel(this->m_ClProgram, "ckDMAS", &clErr); break; } case BeamformingSettings::BeamformingAlgorithm::sDMAS: { this->m_PixelCalculation = clCreateKernel(this->m_ClProgram, "cksDMAS", &clErr); break; } default: { MITK_INFO << "No beamforming algorithm specified, setting to DAS"; this->m_PixelCalculation = clCreateKernel(this->m_ClProgram, "ckDAS", &clErr); break; } } buildErr |= CHECK_OCL_ERR( clErr ); } CHECK_OCL_ERR(clErr); return (OclFilter::IsInitialized() && buildErr ); } void mitk::PhotoacousticOCLBeamformingFilter::SetInput(mitk::Image::Pointer image) { OclDataSetToDataSetFilter::SetInput(image); m_InputImage = image; m_Conf.inputDim[0] = m_InputImage->GetDimension(0); m_Conf.inputDim[1] = m_InputImage->GetDimension(1); m_Conf.inputDim[2] = m_InputImage->GetDimension(2); } void mitk::PhotoacousticOCLBeamformingFilter::SetInput(void* data, unsigned int* dimensions, unsigned int BpE) { OclDataSetToDataSetFilter::SetInput(data, dimensions[0] * dimensions[1] * dimensions[2], BpE); m_Conf.inputDim[0] = dimensions[0]; m_Conf.inputDim[1] = dimensions[1]; m_Conf.inputDim[2] = dimensions[2]; } mitk::Image::Pointer mitk::PhotoacousticOCLBeamformingFilter::GetOutputAsImage() { mitk::Image::Pointer outputImage = mitk::Image::New(); if (m_Output->IsModified(GPU_DATA)) { void* pData = m_Output->TransferDataToCPU(m_CommandQue); const unsigned int dimension = 3; unsigned int dimensions[3] = { (unsigned int)m_OutputDim[0], (unsigned int)m_OutputDim[1], (unsigned int)m_OutputDim[2] }; const mitk::SlicedGeometry3D::Pointer p_slg = m_InputImage->GetSlicedGeometry(); MITK_DEBUG << "Creating new MITK Image."; outputImage->Initialize(this->GetOutputType(), dimension, dimensions); outputImage->SetSpacing(p_slg->GetSpacing()); outputImage->SetImportVolume(pData, 0, 0, mitk::Image::ImportMemoryManagementType::ManageMemory); } MITK_DEBUG << "Image Initialized."; return outputImage; } void* mitk::PhotoacousticOCLBeamformingFilter::GetOutput() { return OclDataSetToDataSetFilter::GetOutput(); } #endif diff --git a/Modules/PhotoacousticsAlgorithms/source/mitkPhotoacousticImage.cpp b/Modules/PhotoacousticsAlgorithms/source/mitkPhotoacousticImage.cpp index f498dcb70b..c74336ba67 100644 --- a/Modules/PhotoacousticsAlgorithms/source/mitkPhotoacousticImage.cpp +++ b/Modules/PhotoacousticsAlgorithms/source/mitkPhotoacousticImage.cpp @@ -1,533 +1,541 @@ /*=================================================================== 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. ===================================================================*/ #define _USE_MATH_DEFINES #include #include "mitkPhotoacousticImage.h" #include "../ITKFilter/ITKUltrasound/itkBModeImageFilter.h" #include "../ITKFilter/itkPhotoacousticBModeImageFilter.h" #include "mitkImageCast.h" #include "mitkITKImageImport.h" #include "mitkPhotoacousticBeamformingFilter.h" #include #include #include "./OpenCLFilter/mitkPhotoacousticBModeFilter.h" // itk dependencies #include "itkImage.h" #include "itkResampleImageFilter.h" #include "itkCastImageFilter.h" #include "itkCropImageFilter.h" #include "itkRescaleIntensityImageFilter.h" #include "itkIntensityWindowingImageFilter.h" #include #include "itkMultiplyImageFilter.h" #include "itkBSplineInterpolateImageFunction.h" #include // needed itk image filters #include "mitkITKImageImport.h" #include "itkFFTShiftImageFilter.h" #include "itkMultiplyImageFilter.h" #include "itkComplexToModulusImageFilter.h" #include #include "../ITKFilter/ITKUltrasound/itkFFT1DComplexConjugateToRealImageFilter.h" #include "../ITKFilter/ITKUltrasound/itkFFT1DRealToComplexConjugateImageFilter.h" mitk::PhotoacousticImage::PhotoacousticImage() : m_BeamformingFilter(BeamformingFilter::New()) { MITK_INFO << "[PhotoacousticImage Debug] created that image"; } mitk::PhotoacousticImage::~PhotoacousticImage() { MITK_INFO << "[PhotoacousticImage Debug] destroyed that image"; } mitk::Image::Pointer mitk::PhotoacousticImage::ApplyBmodeFilter(mitk::Image::Pointer inputImage, BModeMethod method, bool UseGPU, bool UseLogFilter, float resampleSpacing) { // the image needs to be of floating point type for the envelope filter to work; the casting is done automatically by the CastToItkImage typedef itk::Image< float, 3 > itkFloatImageType; typedef itk::IdentityTransform TransformType; if (method == BModeMethod::Abs) { mitk::Image::Pointer input; mitk::Image::Pointer out; if (inputImage->GetPixelType().GetTypeAsString() == "scalar (float)" || inputImage->GetPixelType().GetTypeAsString() == " (float)") input = inputImage; else input = ApplyCropping(inputImage, 0, 0, 0, 0, 0, inputImage->GetDimension(2) - 1); if (!UseGPU) { PhotoacousticBModeFilter::Pointer filter = PhotoacousticBModeFilter::New(); filter->SetParameters(UseLogFilter); filter->SetInput(input); filter->Update(); out = filter->GetOutput(); if (resampleSpacing == 0) return out; } #ifdef PHOTOACOUSTICS_USE_GPU else { PhotoacousticOCLBModeFilter::Pointer filter = PhotoacousticOCLBModeFilter::New(); filter->SetParameters(UseLogFilter); filter->SetInput(input); filter->Update(); out = filter->GetOutput(); if (resampleSpacing == 0) return out; } #endif typedef itk::ResampleImageFilter < itkFloatImageType, itkFloatImageType > ResampleImageFilter; ResampleImageFilter::Pointer resampleImageFilter = ResampleImageFilter::New(); itkFloatImageType::Pointer itkImage; mitk::CastToItkImage(out, itkImage); itkFloatImageType::SpacingType outputSpacing; itkFloatImageType::SizeType inputSize = itkImage->GetLargestPossibleRegion().GetSize(); itkFloatImageType::SizeType outputSize = inputSize; outputSpacing[0] = itkImage->GetSpacing()[0]; outputSpacing[1] = resampleSpacing; outputSpacing[2] = itkImage->GetSpacing()[2]; outputSize[1] = inputSize[1] * itkImage->GetSpacing()[1] / outputSpacing[1]; typedef itk::IdentityTransform TransformType; resampleImageFilter->SetInput(itkImage); resampleImageFilter->SetSize(outputSize); resampleImageFilter->SetOutputSpacing(outputSpacing); resampleImageFilter->SetTransform(TransformType::New()); resampleImageFilter->UpdateLargestPossibleRegion(); return mitk::GrabItkImageMemory(resampleImageFilter->GetOutput()); } else if (method == BModeMethod::EnvelopeDetection) { typedef itk::BModeImageFilter < itkFloatImageType, itkFloatImageType > BModeFilterType; BModeFilterType::Pointer bModeFilter = BModeFilterType::New(); // LogFilter typedef itk::PhotoacousticBModeImageFilter < itkFloatImageType, itkFloatImageType > PhotoacousticBModeImageFilter; PhotoacousticBModeImageFilter::Pointer photoacousticBModeFilter = PhotoacousticBModeImageFilter::New(); // No LogFilter typedef itk::ResampleImageFilter < itkFloatImageType, itkFloatImageType > ResampleImageFilter; ResampleImageFilter::Pointer resampleImageFilter = ResampleImageFilter::New(); itkFloatImageType::Pointer itkImage; mitk::CastToItkImage(inputImage, itkImage); itkFloatImageType::Pointer bmode; if (UseLogFilter) { bModeFilter->SetInput(itkImage); bModeFilter->SetDirection(1); bmode = bModeFilter->GetOutput(); } else { photoacousticBModeFilter->SetInput(itkImage); photoacousticBModeFilter->SetDirection(1); bmode = photoacousticBModeFilter->GetOutput(); } // resampleSpacing == 0 means: do no resampling if (resampleSpacing == 0) { return mitk::GrabItkImageMemory(bmode); } itkFloatImageType::SpacingType outputSpacing; itkFloatImageType::SizeType inputSize = itkImage->GetLargestPossibleRegion().GetSize(); itkFloatImageType::SizeType outputSize = inputSize; outputSpacing[0] = itkImage->GetSpacing()[0]; outputSpacing[1] = resampleSpacing; outputSpacing[2] = itkImage->GetSpacing()[2]; outputSize[1] = inputSize[1] * itkImage->GetSpacing()[1] / outputSpacing[1]; resampleImageFilter->SetInput(bmode); resampleImageFilter->SetSize(outputSize); resampleImageFilter->SetOutputSpacing(outputSpacing); resampleImageFilter->SetTransform(TransformType::New()); resampleImageFilter->UpdateLargestPossibleRegion(); return mitk::GrabItkImageMemory(resampleImageFilter->GetOutput()); } return nullptr; } /*mitk::Image::Pointer mitk::PhotoacousticImage::ApplyScatteringCompensation(mitk::Image::Pointer inputImage, int scattering) { typedef itk::Image< float, 3 > itkFloatImageType; typedef itk::MultiplyImageFilter MultiplyImageFilterType; itkFloatImageType::Pointer itkImage; mitk::CastToItkImage(inputImage, itkImage); MultiplyImageFilterType::Pointer multiplyFilter = MultiplyImageFilterType::New(); multiplyFilter->SetInput1(itkImage); multiplyFilter->SetInput2(m_FluenceCompResizedItk.at(m_ScatteringCoefficient)); return mitk::GrabItkImageMemory(multiplyFilter->GetOutput()); }*/ mitk::Image::Pointer mitk::PhotoacousticImage::ApplyResampling(mitk::Image::Pointer inputImage, unsigned int outputSize[2]) { typedef itk::Image< float, 3 > itkFloatImageType; typedef itk::ResampleImageFilter < itkFloatImageType, itkFloatImageType > ResampleImageFilter; ResampleImageFilter::Pointer resampleImageFilter = ResampleImageFilter::New(); typedef itk::LinearInterpolateImageFunction T_Interpolator; itkFloatImageType::Pointer itkImage; mitk::CastToItkImage(inputImage, itkImage); itkFloatImageType::SpacingType outputSpacingItk; itkFloatImageType::SizeType inputSizeItk = itkImage->GetLargestPossibleRegion().GetSize(); itkFloatImageType::SizeType outputSizeItk = inputSizeItk; outputSizeItk[0] = outputSize[0]; outputSizeItk[1] = outputSize[1]; outputSizeItk[2] = inputSizeItk[2]; outputSpacingItk[0] = itkImage->GetSpacing()[0] * (static_cast(inputSizeItk[0]) / static_cast(outputSizeItk[0])); outputSpacingItk[1] = itkImage->GetSpacing()[1] * (static_cast(inputSizeItk[1]) / static_cast(outputSizeItk[1])); outputSpacingItk[2] = itkImage->GetSpacing()[2]; typedef itk::IdentityTransform TransformType; T_Interpolator::Pointer _pInterpolator = T_Interpolator::New(); resampleImageFilter->SetInput(itkImage); resampleImageFilter->SetSize(outputSizeItk); resampleImageFilter->SetOutputSpacing(outputSpacingItk); resampleImageFilter->SetTransform(TransformType::New()); resampleImageFilter->SetInterpolator(_pInterpolator); resampleImageFilter->UpdateLargestPossibleRegion(); return mitk::GrabItkImageMemory(resampleImageFilter->GetOutput()); } mitk::Image::Pointer mitk::PhotoacousticImage::ApplyCropping(mitk::Image::Pointer inputImage, int above, int below, int right, int left, int minSlice, int maxSlice) { unsigned int inputDim[3] = { inputImage->GetDimension(0), inputImage->GetDimension(1), inputImage->GetDimension(2) }; unsigned int outputDim[3] = { inputImage->GetDimension(0) - left - right, inputImage->GetDimension(1) - (unsigned int)above - (unsigned int)below, (unsigned int)maxSlice - (unsigned int)minSlice + 1 }; void* inputData; float* outputData = new float[outputDim[0] * outputDim[1] * outputDim[2]]; ImageReadAccessor acc(inputImage); inputData = const_cast(acc.GetData()); // convert the data to float by default // as of now only float, short, double are used at all. if (inputImage->GetPixelType().GetTypeAsString() == "scalar (float)" || inputImage->GetPixelType().GetTypeAsString() == " (float)") { // copy the data into the cropped image for (unsigned short sl = 0; sl < outputDim[2]; ++sl) { for (unsigned short l = 0; l < outputDim[0]; ++l) { for (unsigned short s = 0; s < outputDim[1]; ++s) { outputData[l + s*(unsigned short)outputDim[0] + sl*outputDim[0] * outputDim[1]] = (float)((float*)inputData)[(l + left) + (s + above)*(unsigned short)inputDim[0] + (sl + minSlice)*inputDim[0] * inputDim[1]]; } } } } else if (inputImage->GetPixelType().GetTypeAsString() == "scalar (short)" || inputImage->GetPixelType().GetTypeAsString() == " (short)") { // copy the data to the cropped image for (unsigned short sl = 0; sl < outputDim[2]; ++sl) { for (unsigned short l = 0; l < outputDim[0]; ++l) { for (unsigned short s = 0; s < outputDim[1]; ++s) { outputData[l + s*(unsigned short)outputDim[0] + sl*outputDim[0] * outputDim[1]] = (float)((short*)inputData)[(l + left) + (s + above)*(unsigned short)inputDim[0] + (sl + minSlice)*inputDim[0] * inputDim[1]]; } } } } else if (inputImage->GetPixelType().GetTypeAsString() == "scalar (double)" || inputImage->GetPixelType().GetTypeAsString() == " (double)") { // copy the data to the cropped image for (unsigned short sl = 0; sl < outputDim[2]; ++sl) { for (unsigned short l = 0; l < outputDim[0]; ++l) { for (unsigned short s = 0; s < outputDim[1]; ++s) { outputData[l + s*(unsigned short)outputDim[0] + sl*outputDim[0] * outputDim[1]] = (float)((double*)inputData)[(l + left) + (s + above)*(unsigned short)inputDim[0] + (sl + minSlice)*inputDim[0] * inputDim[1]]; } } } } else { MITK_INFO << "Could not determine pixel type"; } mitk::Image::Pointer output = mitk::Image::New(); output->Initialize(mitk::MakeScalarPixelType(), 3, outputDim); output->SetSpacing(inputImage->GetGeometry()->GetSpacing()); output->SetImportVolume(outputData, 0, 0, mitk::Image::ReferenceMemory); return output; } mitk::Image::Pointer mitk::PhotoacousticImage::ApplyBeamforming(mitk::Image::Pointer inputImage, BeamformingSettings config, std::string& message, std::function progressHandle) { Image::Pointer processedImage = inputImage; if (inputImage->GetDimension() != 3) { processedImage->Initialize(mitk::MakeScalarPixelType(), 3, inputImage->GetDimensions()); processedImage->SetSpacing(inputImage->GetGeometry()->GetSpacing()); mitk::ImageReadAccessor copy(inputImage); processedImage->SetImportVolume(copy.GetData()); } config.RecordTime = config.RecordTime - (float)(config.upperCutoff) / (float)inputImage->GetDimension(1) * config.RecordTime; // adjust the recorded time lost by cropping progressHandle(0, "converting image"); if (!config.partial) { config.CropBounds[0] = 0; config.CropBounds[1] = inputImage->GetDimension(2) - 1; } processedImage = ApplyCropping(inputImage, config.upperCutoff, 0, 0, 0, config.CropBounds[0], config.CropBounds[1]); config.inputDim[0] = processedImage->GetDimension(0); config.inputDim[1] = processedImage->GetDimension(1); config.inputDim[2] = processedImage->GetDimension(2); // perform the beamforming m_BeamformingFilter->SetInput(processedImage); m_BeamformingFilter->Configure(config); m_BeamformingFilter->SetProgressHandle(progressHandle); m_BeamformingFilter->UpdateLargestPossibleRegion(); processedImage = m_BeamformingFilter->GetOutput(); message = m_BeamformingFilter->GetMessageString(); return processedImage; } mitk::Image::Pointer mitk::PhotoacousticImage::BandpassFilter(mitk::Image::Pointer data, float recordTime, float BPHighPass, float BPLowPass, float alpha) { bool powerOfTwo = false; int finalPower = 0; for (int i = 1; pow(2, i) <= data->GetDimension(1); ++i) { finalPower = i; if (pow(2, i) == data->GetDimension(1)) { powerOfTwo = true; } } if (!powerOfTwo) { unsigned int dim[2] = { data->GetDimension(0), (unsigned int)pow(2,finalPower+1)}; data = ApplyResampling(data, dim); } MITK_INFO << data->GetDimension(0); // do a fourier transform, multiply with an appropriate window for the filter, and transform back typedef float PixelType; typedef itk::Image< PixelType, 3 > RealImageType; RealImageType::Pointer image; mitk::CastToItkImage(data, image); typedef itk::FFT1DRealToComplexConjugateImageFilter ForwardFFTFilterType; typedef ForwardFFTFilterType::OutputImageType ComplexImageType; ForwardFFTFilterType::Pointer forwardFFTFilter = ForwardFFTFilterType::New(); forwardFFTFilter->SetInput(image); forwardFFTFilter->SetDirection(1); try { forwardFFTFilter->UpdateOutputInformation(); } catch (itk::ExceptionObject & error) { std::cerr << "Error: " << error << std::endl; MITK_WARN << "Bandpass could not be applied"; return data; } float singleVoxel = 1 / (recordTime / data->GetDimension(1)) / 2 / 1000; float cutoffPixelHighPass = std::min(BPHighPass / singleVoxel, (float)data->GetDimension(1) / 2); float cutoffPixelLowPass = std::min(BPLowPass / singleVoxel, (float)data->GetDimension(1) / 2 - cutoffPixelHighPass); RealImageType::Pointer fftMultiplicator = BPFunction(data, cutoffPixelHighPass, cutoffPixelLowPass, alpha); typedef itk::MultiplyImageFilter< ComplexImageType, RealImageType, ComplexImageType > MultiplyFilterType; MultiplyFilterType::Pointer multiplyFilter = MultiplyFilterType::New(); multiplyFilter->SetInput1(forwardFFTFilter->GetOutput()); multiplyFilter->SetInput2(fftMultiplicator); /*itk::ComplexToModulusImageFilter::Pointer toReal = itk::ComplexToModulusImageFilter::New(); toReal->SetInput(forwardFFTFilter->GetOutput()); return GrabItkImageMemory(toReal->GetOutput()); return GrabItkImageMemory(fftMultiplicator); *///DEBUG typedef itk::FFT1DComplexConjugateToRealImageFilter< ComplexImageType, RealImageType > InverseFilterType; InverseFilterType::Pointer inverseFFTFilter = InverseFilterType::New(); inverseFFTFilter->SetInput(multiplyFilter->GetOutput()); inverseFFTFilter->SetDirection(1); return GrabItkImageMemory(inverseFFTFilter->GetOutput()); } itk::Image::Pointer mitk::PhotoacousticImage::BPFunction(mitk::Image::Pointer reference, int cutoffFrequencyPixelHighPass, int cutoffFrequencyPixelLowPass, float alpha) { float* imageData = new float[reference->GetDimension(0)*reference->GetDimension(1)]; // tukey window float width = reference->GetDimension(1) / 2 - (float)cutoffFrequencyPixelHighPass - (float)cutoffFrequencyPixelLowPass; float center = (float)cutoffFrequencyPixelHighPass / 2 + width / 2; MITK_INFO << width << "width " << center << "center " << alpha; for (unsigned int n = 0; n < reference->GetDimension(1); ++n) { imageData[reference->GetDimension(0)*n] = 0; } - - for (int n = 0; n < width; ++n) + if (alpha < 0.00001) { - if (n <= (alpha*(width - 1)) / 2) - { - imageData[reference->GetDimension(0)*(int)(n + center - (width / 2))] = (1 + cos(M_PI*(2 * n / (alpha*(width - 1)) - 1))) / 2; - } - else if (n >= (width - 1)*(1 - alpha / 2) && n <= (width - 1)) + for (int n = 0; n < width; ++n) { - imageData[reference->GetDimension(0)*(int)(n + center - (width / 2))] = (1 + cos(M_PI*(2 * n / (alpha*(width - 1)) + 1 - 2 / alpha))) / 2; + if (n <= (alpha*(width - 1)) / 2) + { + imageData[reference->GetDimension(0)*(int)(n + center - (width / 2))] = (1 + cos(M_PI*(2 * n / (alpha*(width - 1)) - 1))) / 2; + } + else if (n >= (width - 1)*(1 - alpha / 2)) + { + imageData[reference->GetDimension(0)*(int)(n + center - (width / 2))] = (1 + cos(M_PI*(2 * n / (alpha*(width - 1)) + 1 - 2 / alpha))) / 2; + } + else + { + imageData[reference->GetDimension(0)*(int)(n + center - (width / 2))] = 1; + } } - else + } + else + { + for (int n = 0; n < width; ++n) { imageData[reference->GetDimension(0)*(int)(n + center - (width / 2))] = 1; } } - // Butterworth-Filter /* // first, write the HighPass if (cutoffFrequencyPixelHighPass != reference->GetDimension(1) / 2) { for (int n = 0; n < reference->GetDimension(1) / 2; ++n) { imageData[reference->GetDimension(0)*n] = 1 / (1 + pow( (float)n / (float)(reference->GetDimension(1) / 2 - cutoffFrequencyPixelHighPass) , 2 * butterworthOrder)); } } else { for (int n = 0; n < reference->GetDimension(1) / 2; ++n) { imageData[reference->GetDimension(0)*n] = 1; } } // now, the LowPass for (int n = 0; n < reference->GetDimension(1) / 2; ++n) { imageData[reference->GetDimension(0)*n] *= 1 / (1 + pow( (float)(reference->GetDimension(1) / 2 - 1 - n) / (float)(reference->GetDimension(1) / 2 - cutoffFrequencyPixelLowPass) , 2 * butterworthOrder)); } */ // mirror the first half of the image for (unsigned int n = reference->GetDimension(1) / 2; n < reference->GetDimension(1); ++n) { imageData[reference->GetDimension(0)*n] = imageData[(reference->GetDimension(1) - (n + 1)) * reference->GetDimension(0)]; } // copy and paste to all lines for (unsigned int line = 1; line < reference->GetDimension(0); ++line) { for (unsigned int sample = 0; sample < reference->GetDimension(1); ++sample) { imageData[reference->GetDimension(0)*sample + line] = imageData[reference->GetDimension(0)*sample]; } } typedef itk::Image< float, 3U > ImageType; ImageType::RegionType region; ImageType::IndexType start; start.Fill(0); region.SetIndex(start); ImageType::SizeType size; size[0] = reference->GetDimension(0); size[1] = reference->GetDimension(1); size[2] = reference->GetDimension(2); region.SetSize(size); ImageType::SpacingType SpacingItk; SpacingItk[0] = reference->GetGeometry()->GetSpacing()[0]; SpacingItk[1] = reference->GetGeometry()->GetSpacing()[1]; SpacingItk[2] = reference->GetGeometry()->GetSpacing()[2]; ImageType::Pointer image = ImageType::New(); image->SetRegions(region); image->Allocate(); image->FillBuffer(itk::NumericTraits::Zero); image->SetSpacing(SpacingItk); ImageType::IndexType pixelIndex; for (ImageType::IndexValueType slice = 0; slice < reference->GetDimension(2); ++slice) { for (ImageType::IndexValueType line = 0; line < reference->GetDimension(0); ++line) { for (ImageType::IndexValueType sample = 0; sample < reference->GetDimension(1); ++sample) { pixelIndex[0] = line; pixelIndex[1] = sample; pixelIndex[2] = slice; image->SetPixel(pixelIndex, imageData[line + sample*reference->GetDimension(0)]); } } } delete[] imageData; return image; } diff --git a/Plugins/org.mitk.gui.qt.photoacoustics.imageprocessing/documentation/UserManual/Manual.dox b/Plugins/org.mitk.gui.qt.photoacoustics.imageprocessing/documentation/UserManual/Manual.dox index dcbc432cb7..0762e7beb5 100644 --- a/Plugins/org.mitk.gui.qt.photoacoustics.imageprocessing/documentation/UserManual/Manual.dox +++ b/Plugins/org.mitk.gui.qt.photoacoustics.imageprocessing/documentation/UserManual/Manual.dox @@ -1,35 +1,55 @@ /** \page org_mitk_gui_qt_photoacoustics_imageprocessing The Photoacoustics Imageprocessing Plugin \imageMacro{icon.png,"Icon of Imageprocessing",2.00} \tableofcontents \section org_mitk_gui_qt_photoacoustics_imageprocessingOverview Overview This plugin offers an interface to perform image processing on photoacoustic, as well as ultrasound images, i.e. to use beamforming and post-processing filters. For convenience, image processing can be done automatically for a whole batch of files containing PA or US data. + \section org_mitk_gui_qt_photoacoustics_imageprocessingPrerequisites Prerequisites -To use the much faster openCL filters which run on the graphics card, MITK has to be able to use openCL, so it is necessary to install the openCL implementation provided by your graphics card vendor. +To use the much more performant openCL filters which run on the graphics card, MITK has to be able to use openCL, for which it is necessary to install the openCL implementation provided by your graphics card vendor. + \section org_mitk_gui_qt_photoacoustics_imageprocessingFiltering Using the filters To perform image processing, simply load an image into MITK and select it in the Data manager. Only the selected image will be processed by the filters. \imageMacro{QmikPhotoacousticsImageProcessing_DataManager.png,"Select the image to be processed",7.62} -before performing reconstruction or using other filters those can be configured using the plugin's settings panel. +Before performing reconstruction or using other filters those can be configured using the plugin's settings panel. \imageMacro{QmikPhotoacousticsImageProcessing_Settings.png,"The plugin's GUI",7.62} + \subsection org_mitk_gui_qt_photoacoustics_imageprocessingBeamforming The Beamforming Settings For beamforming, three beamforming algorithms are available:
  • DAS (Delay And Sum)
  • DMAS (Delay Multiply And Sum)
  • sDMAS (signed Delay Multiply And Sum)
-Each of those can be coupled with either spherical delay calculation or a quadratic approximation for the delays. -Other Standard beamforming parameters are available. The Plugin is able to calculate the used scan depth as well as the transducer pitch from the selected image if the time-axis spacing is in microseconds, and the horizontal spacing in mm. +Each of those can be coupled with either spherical delay calculation or a quadratic approximation for the delays. To supress noise, one of the following apodizations can be chosen to be used when beamforming: +
    +
  • Box (No apodization) +
  • Hamming +
  • Von Hann +
+Other Standard beamforming parameters are available, which have to be chosen depending on the source image to attain a correctly reconstructed image. +The Plugin is able to calculate the used scan depth as well as the transducer pitch from the selected image if the time-axis spacing is in microseconds, and the horizontal spacing in mm. If such a spacing is given, +check the box "Auto Get Depth" to make the plugin read those values by itself. +If the US source or the laser used for imaging is not located at the top of the image, an option is given to cut off pixels at the top of the image until the source. This value should be calibrated by the user +to match the used hardware. +If one wishes to beamform only certain slices of a given image, those can be selected by checking "select slices" and setting the "min" and "max" values accordingly, which are to be understood as closed interval boundaries. + \subsection org_mitk_gui_qt_photoacoustics_imageprocessingBandpass The Bandpass Settings +The bandpass uses an itk implementation of an 1D Fast Fourier Transform (FFT) to transform the image vertically, then filters the image using a Tukey window in the frequency domain and performs an inverse 1D FFT to get the filtered image. +The "smoothness" of the tukey window can be chosen by using the "Tukey window alpha" parameter. The Tukey window interpolates between a Box window (alpha = 0) and a Von Hann window (alpha = 1). +The filtered frequencies can be set by defining the High and Low pass frequencies. + \subsection org_mitk_gui_qt_photoacoustics_imageprocessingCrop The Crop Filter Settings + \subsection org_mitk_gui_qt_photoacoustics_imageprocessingBMode The BMode Filter Settings + \subsection org_mitk_gui_qt_photoacoustics_imageprocessingBatch Batch Processing When processing large amounts of data, an option is available to automatically process multiple images by applying all filters in order to them and saving the resulting images. In the first row of the Batch Processing Panel one can select which filters should be applied to the image; in the second row one can select whether the resulting image after the filter should be saved. After pressing the "Start Batch Processing" button, one can choose first the images to be processed, and then the folder where they will be saved. */ diff --git a/Plugins/org.mitk.gui.qt.photoacoustics.imageprocessing/src/internal/PAImageProcessingControls.ui b/Plugins/org.mitk.gui.qt.photoacoustics.imageprocessing/src/internal/PAImageProcessingControls.ui index 7883dd2171..088581d194 100644 --- a/Plugins/org.mitk.gui.qt.photoacoustics.imageprocessing/src/internal/PAImageProcessingControls.ui +++ b/Plugins/org.mitk.gui.qt.photoacoustics.imageprocessing/src/internal/PAImageProcessingControls.ui @@ -1,991 +1,991 @@ PAImageProcessingControls 0 0 382 1278 0 0 QmitkTemplate <html><head/><body><p><span style=" font-weight:600;">Batch Processing</span></p></body></html> Start Batch Processing Bandpass true Crop true Save true Save true Save Beamform true BMode true Save true <html><head/><body><p><span style=" font-weight:600;">B-mode Filter Settings</span></p></body></html> Do Resampling true - Envelope Detection + Absolute Filter Absolute Filter Envelope Detection 0 0 13 0 11 3 0.010000000000000 1.000000000000000 0.010000000000000 0.075000000000000 [mm] Depth Spacing Add Logfilter Use GPU QLabel { color: rgb(255, 0, 0) } <html><head/><body><p align="center"><span style=" font-size:10pt; font-weight:600;">Please select an image!</span></p></body></html> 0 0 Do image processing Apply B-mode Filter Qt::Horizontal <html><head/><body><p><span style=" font-weight:600;">Bandpass Filter Settings</span></p></body></html> QLayout::SetDefaultConstraint 0 0 0 3 0.010000000000000 200.000000000000000 15.000000000000000 [MHz] f High Pass [MHz] f Low Pass 0 0 3 200.000000000000000 - Thukey window alpha + Tukey window alpha 1 200.000000000000000 3000.000000000000000 5.000000000000000 1540.000000000000000 [m/s] Speed of Sound 2 1.000000000000000 0.100000000000000 0.500000000000000 <html><head/><body><p align="center"><span style=" font-size:10pt; font-weight:600; color:#ff0000;">Please select an image!</span></p></body></html> Apply Bandpass Qt::Horizontal <html><head/><body><p><span style=" font-weight:600;">Crop Filter Settings</span></p></body></html> 99999 10 Cut Top Cut Bottom 99999 5 165 <html><head/><body><p align="center"><span style=" font-size:10pt; font-weight:600; color:#ff0000;">Please select an image!</span></p></body></html> Apply Crop Filer Qt::Horizontal <html><head/><body><p><span style=" font-weight:600;">Beamforming Filter Settings</span></p></body></html> 5 2 Delay Calculation Auto Get Depth true Apply Beamforming Beamforming Method [mm] Scan Depth 0 0 3 0.010000000000000 9.000000000000000 0.050000000000000 0.300000000000000 Transducer Elements 0 0 4 300.000000000000000 0.100000000000000 50.000000000000000 [mm] Transducer Pitch 0 0 64 1024 128 128 0 0 256 16384 256 2048 0 0 64 2048 128 256 Samples Reconstruction Lines true 0 0 100 0 0 0 900 10 0 0 0 DAS DMAS sDMAS 0 0 - Spherical Wave + Quad. Approx. Quad. Approx. Spherical Wave 0 0 PA Image US Image Image Type 0 0 Von Hann Hamming Box Apodization 0 0 1 200.000000000000000 3000.000000000000000 5.000000000000000 1540.000000000000000 [m/s] Speed of Sound false 99999 minimal beamformed slice min false 99999 10 Maximal beamformed slice max select slices Compute On GPU true true Auto Use Bandpass 0 0 1 1.000000000000000 180.000000000000000 27.000000000000000 [°] Element Angle Cutoff Upper Voxels <html><head/><body><p align="center"><span style=" font-size:10pt; font-weight:600; color:#ff0000;">Please select an image!</span></p></body></html>