2024
A Unified Approach for Synthesizing Multimodal Brain MR Images via Gated Hybrid Fusion
Cho J, Liu X, Xing F, Ouyang J, Fakhri G, Park J, Woo J. A Unified Approach for Synthesizing Multimodal Brain MR Images via Gated Hybrid Fusion. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2024 DOI: 10.58530/2024/2242.Peer-Reviewed Original ResearchCross noise level PET denoising with continuous adversarial domain generalization
Liu X, Eslahi S, Marin T, Tiss A, Chemli Y, Huang Y, Johnson K, Fakhri G, Ouyang J. Cross noise level PET denoising with continuous adversarial domain generalization. Physics In Medicine And Biology 2024, 69: 085001. PMID: 38484401, PMCID: PMC11195012, DOI: 10.1088/1361-6560/ad341a.Peer-Reviewed Original ResearchDomain generalization techniqueDomain generalizationDenoising performanceSuperior denoising performanceLatent feature representationGeneral techniqueDistribution shiftsAdversarial trainingDenoised imageFeature representationDomain labelsDistribution divergenceNoise levelDeep learningImage spaceDenoisingPerformance degradationCore ideaNoise realizationsCD methodNoiseImage volumesPerformanceImagesPSNRDisentangled multimodal brain MR image translation via transformer-based modality infuser
Cho J, Liu X, Xing F, Ouyang J, Fakhri G, Park J, Woo J. Disentangled multimodal brain MR image translation via transformer-based modality infuser. Progress In Biomedical Optics And Imaging 2024, 12926: 129262h-129262h-6. DOI: 10.1117/12.3006502.Peer-Reviewed Original ResearchConvolutional neural networkBrain tumor segmentation taskModality-specific featuresTumor segmentation taskImage translationAdversarial networkSegmentation taskSynthesis qualityBrain MR imagesNeural networkMR modalitiesAcquired imagesExperimental resultsNetworkGlobal relationshipsDisease diagnosisImagesEncodingBraTSDatasetFeaturesTaskMethodSuperiorityMR imaging
2023
Attenuation correction for PET imaging using conditional denoising diffusion probabilistic model
Dong Y, Jang S, Han P, Johnson K, Ma C, Fakhri G, Li Q, Gong K. Attenuation correction for PET imaging using conditional denoising diffusion probabilistic model. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338188.Peer-Reviewed Original ResearchDiffusion probabilistic modelGenerative adversarial networkConditional encodingAttenuation correctionDenoising diffusion probabilistic modelLow-level featuresProbabilistic modelAttenuation coefficientAdversarial networkExtract featuresPET/MR systemsEncodingPET acquisitionNovel methodDiffusion encodingMagnetic resonanceImagesPET imagingCorrectionMR imagingUNetAttenuationNetworkFeaturesResonanceTauPETGen: Text-Conditional Tau PET Image Synthesis Based on Latent Diffusion Models
Jang S, Gomez C, Thibault E, Becker J, Dong Y, Normandin M, Price J, Johnson K, Fakhri G, Gong K. TauPETGen: Text-Conditional Tau PET Image Synthesis Based on Latent Diffusion Models. 2023, 00: 1-1. DOI: 10.1109/nssmicrtsd49126.2023.10338710.Peer-Reviewed Original ResearchPET 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 levelQuantifying velopharyngeal motion variation in speech sound production using an audio-informed dynamic MRI atlas
Xing F, Jin R, Gilbert I, El Fakhri G, Perry J, Sutton B, Woo J. Quantifying velopharyngeal motion variation in speech sound production using an audio-informed dynamic MRI atlas. Proceedings Of SPIE--the International Society For Optical Engineering 2023, 12464: 124642m-124642m-6. PMID: 37621417, PMCID: PMC10448831, DOI: 10.1117/12.2654082.Peer-Reviewed Original ResearchMotion fieldReal-time speechHigh-dimensional datasetsAudio waveformAtlas spaceTemporal alignmentMotion variationsDatasetMagnetic resonance imagingMotion atlasMotion differencesSpeech variationImage acquisitionTaskSpeechMotion characteristicsDynamic magnetic resonance imagingPrincipal componentsImagesOutlier Robust Disease Classification via Stochastic Confidence Network
Lee K, Lee H, El Fakhri G, Sepulcre J, Liu X, Xing F, Hwang J, Woo J. Outlier Robust Disease Classification via Stochastic Confidence Network. Lecture Notes In Computer Science 2023, 14394: 80-90. DOI: 10.1007/978-3-031-47425-5_8.Peer-Reviewed Original ResearchDeep learningState-of-the-art modelsAccuracy of deep learningState-of-the-artMedical image dataMedical imaging modalitiesImage patchesIrrelevant patchesCategorical featuresPresence of outliersDL modelsConfidence networkConfidence predictionsClassifying outliersData samplesImage dataOutliersExperimental resultsDisease classificationImprove diagnostic performanceClassificationDiagnosing breast tumorsUltrasound imagingPerformanceImages
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 studyImagesMethodSparsityPosterior estimation using deep learning: a simulation study of compartmental modeling in dynamic positron emission tomography
Liu X, Marin T, Amal T, Woo J, Fakhri G, Ouyang J. Posterior estimation using deep learning: a simulation study of compartmental modeling in dynamic positron emission tomography. Medical Physics 2022, 50: 1539-1548. PMID: 36331429, PMCID: PMC10087283, DOI: 10.1002/mp.16078.Peer-Reviewed Original ResearchConceptsConditional variational auto-encoderDeep learning approachNeural networkDeep learningMarkov chain Monte CarloVariational Bayesian inference frameworkLearning approachDeep learning-based approachVariational auto-encoderDeep neural networksLearning-based approachDynamic brain PET imagingPosterior distributionEstimate posterior distributionsBayesian inference frameworkAuto-encoderMedical imagesInference frameworkNetworkSimulation studyBrain PET imagingLearningPosterior estimatesInferior performanceImagesVariational inference for quantifying inter-observer variability in segmentation of anatomical structures
Liu X, Xing F, Marin T, Fakhri G, Woo J. Variational inference for quantifying inter-observer variability in segmentation of anatomical structures. Proceedings Of SPIE--the International Society For Optical Engineering 2022, 12032: 120321m-120321m-6. PMID: 36303579, PMCID: PMC9603619, DOI: 10.1117/12.2604547.Peer-Reviewed Original ResearchSegmentation mapImage dataVariational inference frameworkVariational autoencoder networkMedical image dataInherent information lossMagnetic Resonance (MRSegmentation datasetAutoencoder networkVariational inferenceLatent vectorsInformation lossManual annotationSegmentation methodAleatoric uncertaintyInference frameworkSacrificing accuracyExperimental resultsAnnotationOrgan boundariesInter-observer variabilityImagesELBOMapsSegmentsStructure-aware unsupervised tagged-to-cine MRI synthesis with self disentanglement
Liu X, Xing F, Prince J, Stone M, El Fakhri G, Woo J. Structure-aware unsupervised tagged-to-cine MRI synthesis with self disentanglement. Proceedings Of SPIE--the International Society For Optical Engineering 2022, 12032: 120321q-120321q-7. PMID: 36203947, PMCID: PMC9533681, DOI: 10.1117/12.2610655.Peer-Reviewed Original ResearchStructure feature extractorImage style transferSelf-training schemeStyle transferFeature extractorAdversarial gameSynthesized imagesInformation w.Superior performanceStructural consistencyTask-specificCycle reconstructionStructural encodingImagesDiscoGANCycleGANEncodingExtractorExtraction stepNetworkSchemeGameInput
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 registrationSpeechImagesDual-Cycle Constrained Bijective Vae-Gan For Tagged-To-Cine Magnetic Resonance Image Synthesis
Liu X, Xing F, Prince J, Carass A, Stone M, Fakhri G, Woo J. Dual-Cycle Constrained Bijective Vae-Gan For Tagged-To-Cine Magnetic Resonance Image Synthesis. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2021, 00: 1448-1452. PMID: 34707796, PMCID: PMC8547333, DOI: 10.1109/isbi48211.2021.9433852.Peer-Reviewed Original ResearchMR image synthesisAdversarial trainingImage synthesisVAE-GANMR imagingTagged MR imagesCine MR imagingMoving organsSuperior performanceMagnetic resonance imagingAcquisition timeCycle reconstructionHealthy subjectsResonance imagingAnatomical resolutionComparison methodMotion analysisTagged magnetic resonance imagingTissue segmentationImagesScanning session
2020
Penalized Parametric PET Image Estimation Using Local Linear Fitting
Kim K, Gong K, Moon S, Fakhri G, Normandin M, Li Q. Penalized Parametric PET Image Estimation Using Local Linear Fitting. IEEE Transactions On Radiation And Plasma Medical Sciences 2020, 4: 750-758. DOI: 10.1109/trpms.2020.3024123.Peer-Reviewed Original ResearchReconstructed framesImage estimationGraphical modelsFull-dose imagesStatic imagesParametric imaging methodFunction extractionPhysiological informationImagesPositron emission tomographyLogan graphical modelConventional methodsPatient studiesKinetic parametersSuboptimalityFrameDynamic imagingTwo-tissue compartment model
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 ResearchConceptsSignal-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 resolution
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 groupsDeep networks in identifying CT brain hemorrhage
Helwan A, El-Fakhri G, Sasani H, Uzun Ozsahin D. Deep networks in identifying CT brain hemorrhage. Journal Of Intelligent & Fuzzy Systems 2018, Preprint: 1-1. DOI: 10.3233/jifs-172261.Peer-Reviewed Original ResearchConvolutional neural networkStacked autoencoderDeep networksMedical image classificationDeep learning algorithmsMedical expert's experienceImage classificationTraining timeLearning algorithmsNeural networkAutoencoderExpert experienceBrain CT imagesCT imagesNetworkHigher accuracyLess errorAlgorithmImagesAccuracyErrorClassification
2017
A four-dimensional motion field atlas of the tongue from tagged and cine magnetic resonance imaging
Xing F, Prince J, Stone M, Wedeen V, Fakhri G, Woo J. A four-dimensional motion field atlas of the tongue from tagged and cine magnetic resonance imaging. Proceedings Of SPIE--the International Society For Optical Engineering 2017, 10133: 101331h-101331h-6. PMID: 29081569, PMCID: PMC5659618, DOI: 10.1117/12.2254363.Peer-Reviewed Original ResearchMotion fieldDense motion fieldTongue motionAtlas spaceThree-dimensional vector fieldsTagged MR imagesCine imagesImage atlasCine MR imagingAtlas constructionMagnetic resonanceVector fieldsFieldMotionImagesRepresentationQuantitative representationMR imagingAtlasDeformation fieldInter-subject variabilityResonanceCine magnetic resonance imagingInter-subject variationTensor
2016
Direct Parametric Imaging of Reversible Tracers Using Partial Dynamic Data
Kim K, Fakhri G, Li Q. Direct Parametric Imaging of Reversible Tracers Using Partial Dynamic Data. 2016, 1-4. DOI: 10.1109/nssmic.2016.8069385.Peer-Reviewed Original Research