2024
Accelerated 3D metabolite T1 mapping of the brain using variable‐flip‐angle SPICE
Zhao Y, Li Y, Guo R, Jin W, Sutton B, Ma C, Fakhri G, Li Y, Luo J, Liang Z. Accelerated 3D metabolite T1 mapping of the brain using variable‐flip‐angle SPICE. Magnetic Resonance In Medicine 2024, 92: 1310-1322. PMID: 38923032, DOI: 10.1002/mrm.30200.Peer-Reviewed Original ResearchMeSH KeywordsAdultAlgorithmsBrainBrain MappingFemaleHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingMagnetic Resonance SpectroscopyMalePhantoms, ImagingReproducibility of ResultsConceptsLow-rank tensor modelGeneralized series modelMetabolite TExperimental resultsBrain metabolitesClinically acceptable scan timeEfficient encodingPhantom experimental resultsAcceptable scan timeNoisy dataSparse samplingImaging problemsData processingHealthy subject dataVariable flip angleFlip angleTensor modelSaturation effectsQuantitative metabolic imagingMRSI techniquePhantomScan timeData acquisitionMetabolic imagingT1 mapping
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 ResearchMeSH KeywordsArteriesBrainImage Processing, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingPerfusionPerfusion ImagingSpin LabelsConceptsOff-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
2022
Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling
Djebra Y, Marin T, Han P, Bloch I, Fakhri G, Ma C. Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling. IEEE Transactions On Medical Imaging 2022, 42: 158-169. PMID: 36121938, PMCID: PMC10024645, DOI: 10.1109/tmi.2022.3207774.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsComputer SimulationImage Processing, Computer-AssistedMagnetic Resonance ImagingModels, TheoreticalConceptsSpace alignmentSampled k-space dataState-of-the-art methodsIntrinsic low-dimensional manifold structureNumerical simulation studyLow-dimensional manifold structureState-of-the-artLinear subspace modelSparsity modelModel-based frameworkSubspace modelManifold structureMathematical modelManifold modelSparse samplingImage reconstructionMRI applicationsDynamic magnetic resonance imagingSpatiotemporal signalsSpatial resolutionPerformanceSimulation studyImagesMethodSparsity
2020
Motion correction for PET data using subspace-based real-time MR imaging in simultaneous PET/MR
Marin T, Djebra Y, Han P, Chemli Y, Bloch I, Fakhri G, Ouyang J, Petibon Y, Ma C. Motion correction for PET data using subspace-based real-time MR imaging in simultaneous PET/MR. Physics In Medicine And Biology 2020, 65: 235022. PMID: 33263317, PMCID: PMC7985095, DOI: 10.1088/1361-6560/abb31d.Peer-Reviewed Original ResearchMeSH KeywordsArtifactsHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMovementMultimodal ImagingPositron-Emission TomographyTime FactorsConceptsPositron emission tomography reconstructionMotion-corrected PET reconstructionsPET reconstructionMotion-corrected PET imagesIrregular respiratory motionMotion fieldMotion correction methodMotion correction approachIrregular motion patternsUndersampled k-space dataImage quality of positron emission tomographyQuality of positron emission tomographyMotion patternsLow-rank characteristicsRespiratory motionContrast-to-noise ratioEstimated motion fieldSurrogate signalsMotion correctionK-space dataImage qualityReal-time MR imagingSimultaneous PET/MRMotion artifact reductionPET/MR scannersAttenuation correction using deep Learning and integrated UTE/multi-echo Dixon sequence: evaluation in amyloid and tau PET imaging
Gong K, Han P, Johnson K, El Fakhri G, Ma C, Li Q. Attenuation correction using deep Learning and integrated UTE/multi-echo Dixon sequence: evaluation in amyloid and tau PET imaging. European Journal Of Nuclear Medicine And Molecular Imaging 2020, 48: 1351-1361. PMID: 33108475, PMCID: PMC8411350, DOI: 10.1007/s00259-020-05061-w.Peer-Reviewed Original ResearchMeSH KeywordsDeep LearningHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMultimodal ImagingPositron-Emission TomographyTomography, X-Ray ComputedConceptsAttenuation correctionResultsThe Dice coefficientPseudo-CT imagesMR-based AC methodsAccurate ACAC accuracyPET imagingDice coefficientQuantitative accuracyAtlas methodAC methodGradient echoNear verticesTau imagingTau PET imagingAlzheimer's diseaseUltrashortCorrectionTau pathologyRapid acquisitionDeep learning methodsMonitoring of Alzheimer’s diseasePET/MRAmyloidAccelerated J‐resolved 1H‐MRSI with limited and sparse sampling of (‐space
Tang L, Zhao Y, Li Y, Guo R, Clifford B, Fakhri G, Ma C, Liang Z, Luo J. Accelerated J‐resolved 1H‐MRSI with limited and sparse sampling of (‐space. Magnetic Resonance In Medicine 2020, 85: 30-41. PMID: 32726510, PMCID: PMC7992196, DOI: 10.1002/mrm.28413.Peer-Reviewed Original ResearchMR‐based PET attenuation correction using a combined ultrashort echo time/multi‐echo Dixon acquisition
Han P, Horng D, Gong K, Petibon Y, Kim K, Li Q, Johnson K, Fakhri G, Ouyang J, Ma C. MR‐based PET attenuation correction using a combined ultrashort echo time/multi‐echo Dixon acquisition. Medical Physics 2020, 47: 3064-3077. PMID: 32279317, PMCID: PMC7375929, DOI: 10.1002/mp.14180.Peer-Reviewed Original ResearchMeSH KeywordsHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingPhantoms, ImagingPositron-Emission TomographyTomography, X-Ray ComputedConceptsLinear attenuation coefficientPositron emission tomography attenuation correctionPhysical compartmental modelAttenuation correctionShort T<sub>2</sub> componentPET attenuation correctionRadial k-space trajectoryMagnetic resonance (MR)-based methodK-space trajectoriesRadial trajectoryK-spaceAttenuation coefficientDixon acquisitionsPositron emission tomographyWhole white matterMuting methodImage reconstructionImaging speedMR signalMRAC methodPositron emission tomography imagingCorrectionGray matter regionsPhantomMatter regions
2019
Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning
Gong K, Han P, Fakhri G, Ma C, Li Q. Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning. NMR In Biomedicine 2019, 35: e4224. PMID: 31865615, PMCID: PMC7306418, DOI: 10.1002/nbm.4224.Peer-Reviewed Original ResearchMeSH KeywordsBrainDeep LearningHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingSignal-To-Noise RatioSpin LabelsConceptsSignal-to-noise ratioImage denoisingReconstruction frameworkDeep learning-based image denoisingDeep learning-based denoisersMR image denoisingLearning-based denoisingLow signal-to-noise ratioK-space dataNoisy imagesTraining labelsTraining pairsNetwork inputNeural networkDenoisingIn vivo experiment dataSuperior performanceImaging speedReconstruction processImage qualityLong imaging timesNetworkFrameworkImagesSpatial resolutionBody motion detection and correction in cardiac PET: Phantom and human studies
Sun T, Petibon Y, Han P, Ma C, Kim S, Alpert N, Fakhri G, Ouyang J. Body motion detection and correction in cardiac PET: Phantom and human studies. Medical Physics 2019, 46: 4898-4906. PMID: 31508827, PMCID: PMC6842053, DOI: 10.1002/mp.13815.Peer-Reviewed Original ResearchMeSH KeywordsArtifactsFluorodeoxyglucose F18HeartHumansImage Processing, Computer-AssistedMovementPhantoms, ImagingPositron-Emission TomographyConceptsList-mode dataMotion-compensated image reconstructionMotion correctionCenter of massPET list-mode dataMotion correction methodMotion detectionMotion estimationImage reconstructionPatient body motionDegrade image qualityNonrigid registrationImage qualityMotion transformationCoincident distributionBody motion detectionCardiac positron emission tomographyBack-projection techniqueCovariance matrixImage volumesBody motionPositron emission tomographyBack-projectionReference framePhantomMR-based cardiac and respiratory motion correction of PET: application to static and dynamic cardiac 18F-FDG imaging
Petibon Y, Sun T, Han P, Ma C, Fakhri G, Ouyang J. MR-based cardiac and respiratory motion correction of PET: application to static and dynamic cardiac 18F-FDG imaging. Physics In Medicine And Biology 2019, 64: 195009. PMID: 31394518, PMCID: PMC7007962, DOI: 10.1088/1361-6560/ab39c2.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtifactsFluorodeoxyglucose F18Fourier AnalysisHealthy VolunteersHeartHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMotionMultimodal ImagingMyocardiumPositron-Emission TomographyRespirationConceptsMR-based motion correctionRespiratory motion correctionMotion correctionImproved spatial resolutionReconstructed activity concentrationCardiac PET dataSpatial resolutionCoincidence eventsMR-basedPET imagingContrast-to-noise ratioCardiac PET imagingRespiratory phasesMC dataImprove image qualityMR acquisitionQuantitative accuracyCardiac PETPET dataActivity concentrationsMyocardium wallF-FDG PETDynamics studiesImage qualityMotion artifactsFree-Breathing Three-Dimensional T1 Mapping of the Heart Using Subspace-Based Data Acquisition and Image Reconstruction
Han P, Horng D, Marin T, Petibon Y, Ouyang J, Fakhri G, Ma C. Free-Breathing Three-Dimensional T1 Mapping of the Heart Using Subspace-Based Data Acquisition and Image Reconstruction. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2019, 00: 4008-4011. PMID: 31946750, DOI: 10.1109/embc.2019.8856511.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsHeartImage EnhancementImage Processing, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingMyocardiumRespirationConceptsRespiratory motionRespiratory gatingLongitudinal relaxation timeSubspace-based methodsLow-rank tensorMagnetic resonance imagingRelaxation timeT1 mappingT)-spaceSubspace-basedSparsity constraintDynamic MR imagingReconstructed mapsSpatiotemporal correlationThree-dimensionalCardiac MRHealthy subjectsIn vivo dataMagnetizationResonance imagingImage functionMR imagingData acquisitionClinical applicationTensor
2017
A minimum-phase Shinnar-Le Roux spectral-spatial excitation RF pulse for simultaneous water and lipid suppression in 1H-MRSI of body extremities
Han P, Ma C, Deng K, Hu S, Jee K, Ying K, Chen Y, Fakhri G. A minimum-phase Shinnar-Le Roux spectral-spatial excitation RF pulse for simultaneous water and lipid suppression in 1H-MRSI of body extremities. Magnetic Resonance Imaging 2017, 45: 18-25. PMID: 28917812, PMCID: PMC5709164, DOI: 10.1016/j.mri.2017.09.008.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsHumansImage Processing, Computer-AssistedLegLipidsMagnetic Resonance SpectroscopyMuscle, SkeletalPhantoms, ImagingProtonsWaterHigh‐resolution dynamic 31P‐MRSI using a low‐rank tensor model
Ma C, Clifford B, Liu Y, Gu Y, Lam F, Yu X, Liang Z. High‐resolution dynamic 31P‐MRSI using a low‐rank tensor model. Magnetic Resonance In Medicine 2017, 78: 419-428. PMID: 28556373, PMCID: PMC5562044, DOI: 10.1002/mrm.26762.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingPhantoms, ImagingReproducibility of ResultsConceptsLow-rank tensorImage reconstructionHigh-resolution image reconstructionImage functionSubspace structureData acquisitionFrame-ratePursuit approachCorrelation of dataSubspaceK-space coverageK-spaceImagesSNRMathematical structureReconstructionHigh-resolutionModeling purposesIn vivo studiesMethodTensor
2016
Accelerated High-Dimensional MR Imaging With Sparse Sampling Using Low-Rank Tensors
He J, Liu Q, Christodoulou A, Ma C, Lam F, Liang Z. Accelerated High-Dimensional MR Imaging With Sparse Sampling Using Low-Rank Tensors. IEEE Transactions On Medical Imaging 2016, 35: 2119-2129. PMID: 27093543, PMCID: PMC5487008, DOI: 10.1109/tmi.2016.2550204.Peer-Reviewed Original ResearchConceptsLow-rank tensorSparsity constraintImage reconstructionGroup sparsity constraintHigh-dimensional imagesAlternating direction methodCore tensorSubspace estimationData spaceLong data acquisition timeLow-rankUndersampled dataSparse samplingDirection methodData acquisition timeImagesMeasured dataSparsityAcquisition timeConstraintsMathematical structureApplicationsDatasetMRI applicationsSubspace
2015
Improved Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data Corrupted by Noise and <inline-formula><tex-math notation="LaTeX">$B_0$</tex-math></inline-formula> Field Inhomogeneity
Liu Y, Ma C, Clifford B, Lam F, Johnson C, Liang Z. Improved Low-Rank Filtering of Magnetic Resonance Spectroscopic Imaging Data Corrupted by Noise and$B_0$ Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBrainHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingSignal Processing, Computer-AssistedSignal-To-Noise RatioConceptsLow-rank filterSignal-to-noise ratioConstrained Cramer-RaoDenoising MRSI dataFiltering methodLow-rank modelCramer-RaoDenoising performanceRank minimizationHigh-resolution magnetic resonance spectroscopic imagingBoundary constraintsIn vivo MRSI dataData corruptionLow-rankMRSI dataFilterNoiseUpper boundB0 field inhomogeneityField inhomogeneity correctionDenoisingField inhomogeneityInhomogeneity correctionMethodMagnetic resonance spectroscopic imaging
2014
Improved Image Reconstruction for Subspace-Based Spectroscopic Imaging Using Non-Quadratic Regularization
Wu Z, Lam F, Ma C, Liang Z. Improved Image Reconstruction for Subspace-Based Spectroscopic Imaging Using Non-Quadratic Regularization. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2014, 2014: 2432-2435. PMID: 25570481, DOI: 10.1109/embc.2014.6944113.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsComputer SimulationImage Processing, Computer-AssistedMagnetic Resonance SpectroscopyPhantoms, ImagingSignal-To-Noise RatioConceptsImage reconstructionLow-rank modelNon-quadratic regularizationHigh-resolution metabolic imagingSparsely sampled datasetsCapabilities of SPICESPICE frameworkOptimization problemPrimal-dualNon-quadraticImagesSNRAlgorithmDatasetPhantom studySparsenessSpectroscopic imaging methodReconstructionSpectroscopic imagingOptimizationRegularizationMethodCapability