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 ResearchConceptsLow-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
PET image denoising based on denoising diffusion probabilistic model
Gong K, Johnson K, El Fakhri G, Li Q, Pan T. PET image denoising based on denoising diffusion probabilistic model. European Journal Of Nuclear Medicine And Molecular Imaging 2023, 51: 358-368. PMID: 37787849, PMCID: PMC10958486, DOI: 10.1007/s00259-023-06417-8.Peer-Reviewed Original ResearchConceptsDenoising diffusion probabilistic modelPET image denoisingDiffusion probabilistic modelImage denoisingDenoising methodNonlocal meansNetwork inputGenerative adversarial networkData consistency constraintsProbabilistic modelLearning-based modelsAdversarial networkData distributionDenoisingRefinement stepsIterative refinementFlexible frameworkImage qualityPhysical degrading factorsUNetNetworkDatasetImagesInputNoise levelB1 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 equationSuper-resolution in brain positron emission tomography using a real-time motion capture system
Chemli Y, Tétrault M, Marin T, Normandin M, Bloch I, El Fakhri G, Ouyang J, Petibon Y. Super-resolution in brain positron emission tomography using a real-time motion capture system. NeuroImage 2023, 272: 120056. PMID: 36977452, PMCID: PMC10122782, DOI: 10.1016/j.neuroimage.2023.120056.Peer-Reviewed Original ResearchConceptsBrain positron emission tomographySuper-resolutionEvent-by-event basisReal-time motion capture systemSR reconstruction methodTracking cameraVisualization of small structuresPET reconstruction algorithmMoving phantomMeasure target motionLine profilesPET/CT scannerMeasured shiftsImprove image resolutionMotion capture systemMotion tracking devicePositron emission tomographyReconstruction algorithmSpatial resolutionMeasured linesPhantomReal-timeEstimation frameworkIncreased spatial resolutionReconstruction method
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 ResearchConceptsSpace 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 ResearchConceptsSubspace-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 dataAutomation of generative adversarial network-based synthetic data-augmentation for maximizing the diagnostic performance with paranasal imaging
Kong H, Kim J, Moon H, Park H, Kim J, Lim R, Woo J, Fakhri G, Kim D, Kim S. Automation of generative adversarial network-based synthetic data-augmentation for maximizing the diagnostic performance with paranasal imaging. Scientific Reports 2022, 12: 18118. PMID: 36302815, PMCID: PMC9613909, DOI: 10.1038/s41598-022-22222-z.Peer-Reviewed Original ResearchConceptsSynthetic data augmentationData augmentationLack of training dataConventional data augmentationDeep learning methodsTraining dataLearning methodsPipeline approachAlgorithm trainingGraphical dataAutomationWaters' view radiographsModel performanceAutomated pipelinePerformancePerformance parametersAlgorithmDatasetAugmentationDataMethodPipelineRulesIndustrial workers
2021
4D magnetic resonance imaging atlas construction using temporally aligned audio waveforms in speech
Xing F, Jin R, Gilbert I, Perry J, Sutton B, Liu X, Fakhri G, Shosted R, Woo J. 4D magnetic resonance imaging atlas construction using temporally aligned audio waveforms in speech. The Journal Of The Acoustical Society Of America 2021, 150: 3500-3508. PMID: 34852570, PMCID: PMC8580575, DOI: 10.1121/10.0007064.Peer-Reviewed Original ResearchConceptsAudio waveformTemporal domain informationMulti-subject dataAtlas constructionMutual information measureMR image datasetsImage datasetsTarget domainDomain informationPost-processing methodImage sequencesTemporal alignmentSpatiotemporal alignmentMatching patternsInformation measuresImage dataSquare errorAligned volumesAlignment mapOverall score increaseMR technologyCross-correlationDeformable registrationSpeechImagesHigh-Resolution Label-Free Molecular Imaging of Brain Tumor
Guo R, Ma C, Li Y, Zhao Y, Wang T, Li Y, Fakhri G, Liang Z. High-Resolution Label-Free Molecular Imaging of Brain Tumor. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2021, 00: 3049-3052. PMID: 34891886, DOI: 10.1109/embc46164.2021.9630623.Peer-Reviewed Original ResearchConceptsMagnetic resonance spectroscopic imagingBrain tumorsIntra-tumoural metabolic heterogeneityAssessment of treatment efficacySmall-sized tumorsClinical applicationN-acetyl aspartateBrain tumor characterizationPotential clinical applicationsApplication of magnetic resonance spectroscopic imagingTumor characterizationMolecular imaging techniquesBrain metabolitesImaging of brain tumorsTumorTreatment efficacyClinical relevanceMetabolic imagingDiagnosed brain tumorsHigh-resolution metabolic imagingMetabolic heterogeneityTumor detectionMolecular imaging of brain tumorsLabel-free molecular imagingLabel-free molecular imaging techniqueA deep joint sparse non-negative matrix factorization framework for identifying the common and subject-specific functional units of tongue motion during speech
Woo J, Xing F, Prince J, Stone M, Gomez A, Reese T, Wedeen V, El Fakhri G. A deep joint sparse non-negative matrix factorization framework for identifying the common and subject-specific functional units of tongue motion during speech. Medical Image Analysis 2021, 72: 102131. PMID: 34174748, PMCID: PMC8316408, DOI: 10.1016/j.media.2021.102131.Peer-Reviewed Original ResearchConceptsNon-negative matrix factorizationSparse Non-negative Matrix FactorizationIterative shrinkage-thresholding algorithmNon-negative matrix factorization frameworkDeep neural networksMatrix factorization frameworkDeep learning frameworkTongue motionIdentified functional unitsGraph regularizationClustering performanceWeight mapLearning frameworkSpectral clusteringNeural networkMatrix factorizationModular architectureIncreased interpretabilityMotion dataFactorization frameworkConvoluted natureComparison methodTagged magnetic resonance imagingMuscle coordination patternsSpeechA layered single-side readout depth of interaction time-of-flight-PET detector
Bläckberg L, Sajedi S, Fakhri G, Sabet H. A layered single-side readout depth of interaction time-of-flight-PET detector. Physics In Medicine And Biology 2021, 66: 045025. PMID: 33570050, PMCID: PMC8130834, DOI: 10.1088/1361-6560/abd592.Peer-Reviewed Original ResearchConceptsDepth of interactionMulti-pixel photon counterDepth-of-interaction determinationDepth-of-interaction informationTime resolutionTime resolution valuesReduced crystal thicknessNon-DOI detectorsOptical photonsScintillator arrayPET detectorsPhoton counterCrystal pixelsReadout schemeCrystal arrayCrystal thicknessTransport simulationsDetectorPhotodetector arrayReadoutPixel sizePhotodetectorsResolution valuesFirst layerSignal amplitude
2020
Accelerated 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 Research
2019
Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction
Blanc-Durand P, Khalife M, Sgard B, Kaushik S, Soret M, Tiss A, Fakhri G, Habert M, Wiesinger F, Kas A. Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction. PLOS ONE 2019, 14: e0223141. PMID: 31589623, PMCID: PMC6779234, DOI: 10.1371/journal.pone.0223141.Peer-Reviewed Original ResearchConceptsZero echo timeAC mapsAttenuation correctionPET attenuation correctionCT-based ACComputed tomographyAC methodPhoton attenuationZTE-ACInvestigation of suspected dementiaMR imagingBrain computed tomographyAtlas-ACBrain metabolismZTE-MRIConvolutional neural networkEcho timeHead atlasFDG-PET/MRPET imagingLow biasRegions-of-interestPatientsCorrectionNeural networkMR-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 ResearchConceptsRespiratory 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 applicationTensorExploring light confinement in laser-processed LYSO:Ce for photon counting CT application
Bläckberg L, Sajedi S, Mandl S, Mohan A, Vittum B, Fakhri G, Sabet H. Exploring light confinement in laser-processed LYSO:Ce for photon counting CT application. Physics In Medicine And Biology 2019, 64: 095020. PMID: 30897557, PMCID: PMC7191943, DOI: 10.1088/1361-6560/ab1213.Peer-Reviewed Original ResearchConceptsLaser induced optical barriersPhoton counting detectorsLight collection efficiencyCrystal pixelsLYSO:Ce detectorsHigh dose efficiencyPixel arrayCounting detectorsDetector designDose efficiencyOptical barrierPd edgePhotodetector (PDRough interfaceIncreased cross-talkCE detectorCT applicationsDetectorLaser ablationPixel sizeConfinementSmooth ablationLYSOSpatial resolutionCollection efficiencyTime of flight PET reconstruction using nonuniform update for regional recovery uniformity
Kim K, Kim D, Yang J, Fakhri G, Seo Y, Fessler J, Li Q. Time of flight PET reconstruction using nonuniform update for regional recovery uniformity. Medical Physics 2019, 46: 649-664. PMID: 30508255, PMCID: PMC6501218, DOI: 10.1002/mp.13321.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsHumansImage Processing, Computer-AssistedPancreasPositron-Emission TomographyTime FactorsConceptsSignal-to-noise ratio regionVariant step sizeSignal-to-noise ratioNesterov momentumOS-SQSUniform recoveryOS-EMStep sizeNon-TOF PETOrdered subsetsQuad-core CPUEarly stopping criterionGraphics processing unitsTime-of-flight PET reconstructionReconstruction methodPET reconstruction methodsNesterov's momentum methodImage qualityPET reconstructionTOF-PETOverall signal-to-noise ratioActive regionLow activity regionsComputer simulationsRecovery ratio
2018
A Sparse Non-Negative Matrix Factorization Framework for Identifying Functional Units of Tongue Behavior From MRI
Woo J, Prince J, Stone M, Xing F, Gomez A, Green J, Hartnick C, Brady T, Reese T, Wedeen V, Fakhri G. A Sparse Non-Negative Matrix Factorization Framework for Identifying Functional Units of Tongue Behavior From MRI. IEEE Transactions On Medical Imaging 2018, 38: 730-740. PMID: 30235120, PMCID: PMC6422735, DOI: 10.1109/tmi.2018.2870939.Peer-Reviewed Original ResearchConceptsNon-negative matrix factorization frameworkProbabilistic graphical model frameworkMatrix factorization frameworkGraphical model frameworkWeight mapSpectral clusteringSynthetic dataMuscle coordination patternsMatrix factorizationMotion dataMotion patternsTongue motionFactorization frameworkTwo-dimensional imagesMuscle groupsLocal regionsLocal muscle groupLocal structural elementsTagged-MRIImagesFunctional muscle groupsA novel depth-of-interaction rebinning strategy for ultrahigh resolution PET
Kim K, Dutta J, Groll A, Fakhri G, Meng L, Li Q. A novel depth-of-interaction rebinning strategy for ultrahigh resolution PET. Physics In Medicine And Biology 2018, 63: 165011. PMID: 30040073, PMCID: PMC6375090, DOI: 10.1088/1361-6560/aad58c.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAnimalsBrainImage Processing, Computer-AssistedPhantoms, ImagingPositron-Emission TomographyConceptsDepth of interactionReconstructed imagesAlternating direction methodReconstructed image qualityPoisson log-likelihoodImage qualitySub-sampling methodPositron emission tomography systemReduce noise effectsDOI layersReconstruction frameworkDetector pixel sizePoint source experimentsQuadratic surrogatesCdZnTe detectorsAnimal positron emission tomographyLog-likelihoodDirection methodSmall animal positron emission tomographySource ExperimentPhoton countingRebinning methodSystem matrixNoise effectsSinogramPenalized PET Reconstruction Using Deep Learning Prior and Local Linear Fitting
Kim K, Wu D, Gong K, Dutta J, Kim J, Son Y, Kim H, Fakhri G, Li Q. Penalized PET Reconstruction Using Deep Learning Prior and Local Linear Fitting. IEEE Transactions On Medical Imaging 2018, 37: 1478-1487. PMID: 29870375, PMCID: PMC6375088, DOI: 10.1109/tmi.2018.2832613.Peer-Reviewed Original ResearchConceptsDeep learningDenoising convolutional neural networkConvolutional neural networkDeep learning-basedPerformance of iterative reconstructionPotential of deep learningDeep networksNoise levelLearning-basedReconstruction frameworkDegradation of performanceNeural networkDnCNNMedical imagesDownsampled dataFitness functionPoisson thinningFull-dose imagesLow dose imagesNoise conditionsNetworkImage qualityPET reconstructionDose imagesDeep