2023
B1 inhomogeneity‐corrected T1 mapping and quantitative magnetization transfer imaging via simultaneously estimating Bloch‐Siegert shift and magnetization transfer effects
Jang A, Han P, Ma C, Fakhri G, Wang N, Samsonov A, Liu F. B1 inhomogeneity‐corrected T1 mapping and quantitative magnetization transfer imaging via simultaneously estimating Bloch‐Siegert shift and magnetization transfer effects. Magnetic Resonance In Medicine 2023, 90: 1859-1873. PMID: 37427533, PMCID: PMC10528411, DOI: 10.1002/mrm.29778.Peer-Reviewed Original ResearchConceptsBloch-Siegert shiftBloch-SiegertMagnetization transfer effectsMonte Carlo simulationsSpin-lattice relaxationSpin-bath modelMagnetization transferBinary spin-bath modelCarlo simulationsProton fractionOff-resonance irradiationIn vivo brain studiesBloch simulationsPhantom experimentsMagnetizationEstimationTransmitted fieldQuantitative magnetization transferMethod performanceMT effectSignal equationArterial 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 studyImagesMethodSparsityJoint spectral quantification of MR spectroscopic imaging using linear tangent space alignment‐based manifold learning
Ma C, Han P, Zhuo Y, Djebra Y, Marin T, Fakhri G. Joint spectral quantification of MR spectroscopic imaging using linear tangent space alignment‐based manifold learning. Magnetic Resonance In Medicine 2022, 89: 1297-1313. PMID: 36404676, PMCID: PMC9892363, DOI: 10.1002/mrm.29526.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsBrainComputer SimulationHumansMagnetic Resonance ImagingMagnetic Resonance SpectroscopyProton Magnetic Resonance SpectroscopyConceptsSubspace-based methodsManifold learningIntrinsic low-dimensional structureGlobal coordinationLearning-based methodsNumerical simulation dataSpatial smoothness constraintSparsity constraintSpace alignmentSubspace modelSmoothness constraintSuperior performanceRoot mean square errorLinear transformationMechanical simulationsLow-dimensionalSquare errorSubspaceExperimental dataSpectroscopic imagingQuantum mechanical simulationsCoordinate alignmentMR spectroscopic imagingSpectral quantificationSimulated dataUnsupervised arterial spin labeling image superresolution via multiscale generative adversarial network
Cui J, Gong K, Han P, Liu H, Li Q. Unsupervised arterial spin labeling image superresolution via multiscale generative adversarial network. Medical Physics 2022, 49: 2373-2385. PMID: 35048390, DOI: 10.1002/mp.15468.Peer-Reviewed Original ResearchMeSH KeywordsArtifactsHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingSignal-To-Noise RatioSpin LabelsConceptsPeak signal-to-noise ratioStructural similarity indexNearest neighbor interpolationSignal-to-noise ratioTrilinear interpolationNeighbor interpolationAblation studiesB-spline interpolationLow-pass-filterLayer-by-layer trainingLoss termLow resolutionClearer structure boundariesLow signal-to-noise ratioIn vivo datasetsImage superresolutionGAN frameworkAdversarial networkB-spline interpolation methodReduce image noiseWeak labelsPrior informationSimilarity indexDipping methodSimulated data
2021
Free‐breathing 3D cardiac T1 mapping with transmit B1 correction at 3T
Han P, Marin T, Djebra Y, Landes V, Zhuo Y, Fakhri G, Ma C. Free‐breathing 3D cardiac T1 mapping with transmit B1 correction at 3T. Magnetic Resonance In Medicine 2021, 87: 1832-1845. PMID: 34812547, PMCID: PMC8810588, DOI: 10.1002/mrm.29097.Peer-Reviewed Original ResearchMeSH KeywordsHeartHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingPhantoms, ImagingReproducibility of ResultsConceptsFlip-angle estimationCardiac T<sub>1</sub> mappingGradient echo readoutThrough-plane spatial resolutionImaging timePractical imaging timesFree breathingPhantom studyB1 correctionAccelerated imagingIn-planeT)-spaceMyocardial T<sub>1</sub> valuesSubspace-based methodsSpatial resolutionImaging experimentsAcquisition schemeT)-space dataSubject-specific timeCorrectionModified Look-Locker inversion recoveryLook-Locker inversion recoveryTime of data acquisitionAverage imaging timeInversion-recovery sequence
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/MRAmyloidMR‐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 resolutionMR-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 ResearchConceptsMR-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
2016
DC artifact correction for arbitrary phase-cycling sequence
Han P, Park H, Park S. DC artifact correction for arbitrary phase-cycling sequence. Magnetic Resonance Imaging 2016, 38: 21-26. PMID: 27998747, DOI: 10.1016/j.mri.2016.12.015.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsArtifactsBrainElectricityMagnetic Resonance ImagingMaleModels, AnimalPhantoms, ImagingRatsRats, Sprague-DawleySignal Processing, Computer-Assisted
2015
Compressed Sensing for fMRI: Feasibility Study on the Acceleration of Non‐EPI fMRI at 9.4T
Han P, Park S, Kim S, Ye J. Compressed Sensing for fMRI: Feasibility Study on the Acceleration of Non‐EPI fMRI at 9.4T. BioMed Research International 2015, 2015: 131926. PMID: 26413503, PMCID: PMC4564593, DOI: 10.1155/2015/131926.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsBrainFeasibility StudiesImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleRatsRats, Sprague-DawleyConceptsCompressive sensingBalanced steady-state free precessionSensitive to image distortionsHigh-resolution fMRI techniqueMagnetic field inhomogeneityLocal magnetic field inhomogeneitiesConventional functional magnetic resonance imagingCS reconstructionGradient-recalled echoCS algorithmFOCUSS algorithmNon-EPI sequencesMagnetic fieldSampling patternHigh-resolution functional magnetic resonance imagingFunctional magnetic resonance imagingField inhomogeneityGRE-EPIImage distortionSteady-state free precessionExperimental resultsTemporal resolutionAlgorithmFree precessionSpoiled gradient echoPhysiological and Functional Magnetic Resonance Imaging Using Balanced Steady-state Free Precession
Park S, Han P, Choi S. Physiological and Functional Magnetic Resonance Imaging Using Balanced Steady-state Free Precession. Korean Journal Of Radiology 2015, 16: 550-559. PMID: 25995684, PMCID: PMC4435985, DOI: 10.3348/kjr.2015.16.3.550.Peer-Reviewed Original ResearchMeSH KeywordsCervical VertebraeHeadHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingRadiographySignal-To-Noise RatioInvestigation of Inter-Slice Magnetization Transfer Effects as a New Method for MTR Imaging of the Human Brain
Barker J, Han P, Choi S, Bae K, Park S. Investigation of Inter-Slice Magnetization Transfer Effects as a New Method for MTR Imaging of the Human Brain. PLOS ONE 2015, 10: e0117101. PMID: 25664938, PMCID: PMC4321840, DOI: 10.1371/journal.pone.0117101.Peer-Reviewed Original ResearchMeSH KeywordsAdultBrainDiagnostic ImagingHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMagnetsModels, TheoreticalYoung AdultConceptsBalanced steady-state free precessionFlip angleMagnetization transferMagnetization transfer effectsSteady-state free precessionSaturation pulseModel of MTFree precessionMT-weightedAcquisition parametersMT effectMT ratioDelay timePrecessionMTR imagesHigh SNRInterslicePE stepsMagnetizationFlip