2023
Arterial spin labeled perfusion imaging with balanced steady-state free precession readout and radial sampling
Han P, Marin T, Zhuo Y, Ouyang J, El Fakhri G, Ma C. Arterial spin labeled perfusion imaging with balanced steady-state free precession readout and radial sampling. Magnetic Resonance Imaging 2023, 102: 126-132. PMID: 37187264, PMCID: PMC10524790, DOI: 10.1016/j.mri.2023.05.005.Peer-Reviewed Original ResearchConceptsOff-resonance effectsBalanced steady-state free precessionPhase-cycling techniqueTemporal SNRBalanced steady-state free precession acquisitionRadial sampling schemeSpoiled gradient-recalled acquisitionRadial samplingCartesian sampling schemeBalanced steady-state free precession readoutK-space dataSampling schemeSpin labelingSteady-state free precessionK-spaceImage readoutBanding artifactsMotion-related artifactsReadoutFree precessionArterial spin labelingImage reconstructionParallel imagingImaging timePerfusion-weighted imaging
2021
Nonuniform Fast Fourier Transform on Tpus
Lu T, Marin T, Zhuo Y, Chen Y, Ma C. Nonuniform Fast Fourier Transform on Tpus. 2021, 00: 783-787. DOI: 10.1109/isbi48211.2021.9434068.Peer-Reviewed Original ResearchNonuniform fast Fourier transformFast Fourier transformTensor Processing UnitTPU coresFourier transformImage reconstructionMR image reconstructionTensor operatorsK-spaceK-space dataGoogle’s Tensor Processing UnitDeep learning applicationsNumerical examplesNonuniform gridsScaling analysisCPU implementationMagnetic resonanceHardware acceleratorsLearning applicationsComputational bottleneckProcessing unitMatrix multiplicationPractical runtimeAccelerationOperation
2020
Accelerating MRI Reconstruction on TPUs
Lu T, Marin T, Zhuo Y, Chen Y, Ma C. Accelerating MRI Reconstruction on TPUs. 2020, 00: 1-9. DOI: 10.1109/hpec43674.2020.9286192.Peer-Reviewed Original ResearchTensor Processing UnitK-space dataData decompositionMeasured k-space dataImage reconstructionAccelerated MRI reconstructionGoogle’s Tensor Processing UnitMR image reconstructionScientific computing problemsAlternating direction methodMachine learning applicationsReconstruction methodImage reconstruction methodDiscrete Fourier transformSparsifying transformCompressive sensingFourier transform operationSparsity constraintMRI reconstructionLearning applicationsCommunication timeNetwork topologyProcessing unitMatrix multiplicationComputational problems
2011
IMPATIENT MRI: ILLINOIS MASSIVELY PARALLEL ACCELERATION TOOLKIT FOR IMAGE RECONSTRUCTION WITH ENHANCED THROUGHPUT IN MRI
Wu X, Gai J, Lam F, Fu M, Haldar J, Zhuo Y, Liang Z, Hwu W, Sutton B. IMPATIENT MRI: ILLINOIS MASSIVELY PARALLEL ACCELERATION TOOLKIT FOR IMAGE RECONSTRUCTION WITH ENHANCED THROUGHPUT IN MRI. 2011, 1: 69-72. DOI: 10.1109/isbi.2011.5872356.Peer-Reviewed Original ResearchEnhanced throughputImage reconstructionGraphics processing cardsMagnetic field inhomogeneityComputational powerNoisy dataComputing facilitiesComputation timeField inhomogeneityProcessing cardThroughputAcquisition trajectoriesMagnetic resonance imagingPhysical effectsToolkitImagesAdvanced techniquesClinical imagesTemporal resolutionReconstructionChapter 44 Using GPUs to Accelerate Advanced MRI Reconstruction with Field Inhomogeneity Compensation
Zhuo Y, Wu X, Haldar J, Marin T, Hwu W, Liang Z, Sutton B. Chapter 44 Using GPUs to Accelerate Advanced MRI Reconstruction with Field Inhomogeneity Compensation. 2011, 709-722. DOI: 10.1016/b978-0-12-384988-5.00044-9.Peer-Reviewed Original ResearchInhomogeneity compensationNonideal physical effectsReconstruction algorithmMRI reconstruction algorithmsLoop invariant code motionFloating-point computationsMagnetic resonance imagingSingle-precision floating-point computationData acquisition timeAccurate image reconstructionSignal-to-noise ratioGPU implementationGPU kernelsMRI reconstructionSeverity of artifactsImproved trade-offFlexible diagnostic toolConstant memoryGPUCode motionImage contrastPhysical effectsImage reconstructionClinical scansAcquisition time
2010
Sparse regularization in MRI iterative reconstruction using GPUs
Zhuo Y, Sutton B, Wu X, Haldar J, Hwu W, Liang Z. Sparse regularization in MRI iterative reconstruction using GPUs. 2010, 2: 578-582. DOI: 10.1109/bmei.2010.5640008.Peer-Reviewed Original ResearchGraphics processing unitsMR image reconstructionImage reconstructionGraphics processing unit codeIncrease data accessQuadratic regularization termMemory bandwidth bottleneckSparse regularizationRegularization termData accessBandwidth bottleneckImprove image qualityComputational loadProcessing unitRegularization techniqueSpatial regularizationNeighboring voxelsAssociated with frequent communicationImage qualityField inhomogeneity effectsCPUInverse problemComputerFrequent communicationImplementationACCELERATING ITERATIVE FIELD-COMPENSATED MR IMAGE RECONSTRUCTION ON GPUS
Zhuo Y, Wu X, Haldar J, Hwu W, Liang Z, Sutton B. ACCELERATING ITERATIVE FIELD-COMPENSATED MR IMAGE RECONSTRUCTION ON GPUS. 2010, 820-823. DOI: 10.1109/isbi.2010.5490112.Peer-Reviewed Original ResearchGraphics processing unitsMR image reconstructionComputation timeField inhomogeneityImage reconstruction algorithmUnified deviceConjugate gradient algorithmMagnetic field inhomogeneityProcessing unitComputer hardwareMagnetic field mapsImage reconstructionReconstruction algorithmGradient algorithmAlgorithmAir/tissue interfacesInhomogeneity compensationIterative reconstructionComputerCompensation techniqueImplementationSusceptibility differencesImaging systemGpusField mapping