2025
scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links
Wang G, Zhao J, Lin Y, Liu T, Zhao Y, Zhao H. scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links. Nature Communications 2025, 16: 4994. PMID: 40442129, PMCID: PMC12122792, DOI: 10.1038/s41467-025-60333-z.Peer-Reviewed Original ResearchConceptsDeep learning frameworkSingle-cell multi-omics researchSingle-cell multi-omics dataLearning frameworkMulti-omics dataGenerative adversarial networkSingle-cell technologiesData alignmentSingle-cell resolutionMulti-omics researchDownstream analysisCellular statesOmics datasetsAdversarial networkNeural networkProteomic profilingCorrelated featuresBiological informationOmics perspectiveDiverse datasetsFeature topologyDisease mechanismsCell embeddingData resourcesRelationship inferenceTu1640: HIERARCHICAL CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS (GAN) INTEGRATED WITH EVOLUTIONARY SCALE MODELING FOR GENERATING HEPATITIS C VIRUS TARGETED PEPTIDES
Midjani F, Malekpour M, Tofighi S, Khosravi B, Saberzadeh-Ardestani B. Tu1640: HIERARCHICAL CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS (GAN) INTEGRATED WITH EVOLUTIONARY SCALE MODELING FOR GENERATING HEPATITIS C VIRUS TARGETED PEPTIDES. Gastroenterology 2025, 169: s-1880. DOI: 10.1016/s0016-5085(25)05192-3.Peer-Reviewed Original ResearchGenerative adversarial networkConditional generative adversarial network
2024
Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation
Zhou Y, Chen T, Hou J, Xie H, Dvornek N, Zhou S, Wilson D, Duncan J, Liu C, Zhou B. Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation. Medical Image Analysis 2024, 98: 103300. PMID: 39226710, PMCID: PMC11979896, DOI: 10.1016/j.media.2024.103300.Peer-Reviewed Original ResearchGenerative adversarial networkMedical image translationImage translationState-of-the-art methodsImage-to-image translationMedical image datasetsImage translation tasksImage-to-imageState-of-the-artMedical image processingHigh-quality translationsUncertainty estimationCascaded pipelineAdversarial networkImage datasetsSub-tasksTranslation qualityTranslation performanceTranslation tasksImage processingTranslation resultsDM methodPrior imageRobust performanceExperimental resultsCross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer’s Disease Biomarkers
Hassanzadeh R, Abrol A, Hassanzadeh H, Calhoun V. Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer’s Disease Biomarkers. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039975, DOI: 10.1109/embc53108.2024.10781737.Peer-Reviewed Original ResearchConceptsFunctional network connectivityGenerative adversarial networkStructural similarity index measureT1-weighted structural magnetic resonance imaging dataAdversarial networkStructural magnetic resonance imaging dataIncreased functional connectivityMagnetic resonance imaging dataSimilarity index measureCross-modal transformerCross-modal translationPatterns of atrophyAlzheimer's diseaseFunctional connectivityReduced connectivityMotor-visualTemporal regionsWeak supervisionAlzheimer's disease biomarkersControl networkCycle-GANCross-modalAlzheimer patientsContext of Alzheimer's diseaseGeneration approachGray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity
Bi Y, Abrol A, Jia S, Sui J, Calhoun V. Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity. NeuroImage 2024, 297: 120674. PMID: 38851549, DOI: 10.1016/j.neuroimage.2024.120674.Peer-Reviewed Original ResearchFunctional network connectivityMedial prefrontal cortexBrain structuresFunctional network connectivity matricesPrefrontal cortexStructural MRINetwork connectivityGray matterSelf-attention mechanismGenerative adversarial networkDeep learning architectureBrain disordersDorsolateral prefrontal cortexResearch of schizophreniaNeural signal processingIdentified functional connectivityCross-domain analysisAttention mapsStructural biomarkersAdversarial networkLearning architectureDL-PFCICA algorithmSchizophrenia patientsHigh-dimensional fMRI dataTAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction
Guo X, Shi L, Chen X, Liu Q, Zhou B, Xie H, Liu Y, Palyo R, Miller E, Sinusas A, Staib L, Spottiswoode B, Liu C, Dvornek N. TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction. Medical Image Analysis 2024, 96: 103190. PMID: 38820677, PMCID: PMC11180595, DOI: 10.1016/j.media.2024.103190.Peer-Reviewed Original ResearchGenerative adversarial networkAdversarial networkMotion estimation accuracyInter-frame motionIntensity-based image registration techniqueAll-to-oneSegmentation masksImage registration techniquesOriginal frameTemporal informationDiagnosis accuracyMyocardial blood flowEstimation accuracyFrame conversionPositron emission tomographyNovel methodImage qualityPET datasetsRegistration techniqueNetworkCardiac positron emission tomographyBlood flowDynamic cardiac positron emission tomographyMotion correctionCoronary artery diseaseCross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs
Bi Y, Abrol A, Sui J, Calhoun V. Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs. 2024, 00: 1756-1760. DOI: 10.1109/icassp48485.2024.10446450.Peer-Reviewed Original ResearchFunctional network connectivityStructural magnetic resonance imagingCross-modality synthesisFunctional network connectivity matricesGenerative adversarial networkFunctional connectivity networksAdversarial networkSubcortical brain regionsMedical imagesNetwork connectivityFusion of MRIConnectivity networks
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 imagingUNetAttenuationNetworkFeaturesResonancePET 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 levelFast myocardial perfusion SPECT denoising using an attention-guided generative adversarial network
Sun J, Yang B, Li C, Du Y, Liu Y, Wu T, Mok G. Fast myocardial perfusion SPECT denoising using an attention-guided generative adversarial network. Frontiers In Medicine 2023, 10: 1083413. PMID: 36817784, PMCID: PMC9935600, DOI: 10.3389/fmed.2023.1083413.Peer-Reviewed Original ResearchAttention-guided generative adversarial networkGenerative adversarial networkAdversarial networkConvolutional neural network (CNN)-based methodsDeep learning-based denoisersCNN-based networkLearning-based denoisingLocal receptive fieldsReceptive fieldsAttention mechanismConvolution kernelAdam optimizerFive-fold cross-validationAttGANAcquisition timeList mode dataJoint histogramPerfusion defect sizeCGANDefect informationUNetDenoisingNetworkMP-SPECTProjection pairs
2022
Creating High Fidelity Synthetic Pelvis Radiographs Using Generative Adversarial Networks: Unlocking the Potential of Deep Learning Models Without Patient Privacy Concerns
Khosravi B, Rouzrokh P, Mickley J, Faghani S, Larson A, Garner H, Howe B, Erickson B, Taunton M, Wyles C. Creating High Fidelity Synthetic Pelvis Radiographs Using Generative Adversarial Networks: Unlocking the Potential of Deep Learning Models Without Patient Privacy Concerns. The Journal Of Arthroplasty 2022, 38: 2037-2043.e1. PMID: 36535448, DOI: 10.1016/j.arth.2022.12.013.Peer-Reviewed Original ResearchConceptsAdversarial networkSynthetic imagesDL modelsImage fidelityAssessment of image fidelityPerformance of DL modelsGenerative adversarial networkDeep learning modelsCross-institutional sharingArtificial intelligence techniquesPatient privacy concernsPotential of deep learning modelsReal imagesPrivacy concernsDL techniquesIntelligence techniquesRandom imagesLearning modelsPatient privacyPaired imagesReal radiographsData safetyPelvis imagesNetworkHigh-fidelityLow Dose Myocardial Perfusion SPECT Denoising Using an Attention-Based Generative Adversarial Network
Sun J, Li C, Du Y, Wu T, Yang B, Liu Y, Mok G. Low Dose Myocardial Perfusion SPECT Denoising Using an Attention-Based Generative Adversarial Network. 2022, 00: 1-3. DOI: 10.1109/nss/mic44845.2022.10399080.Peer-Reviewed Original ResearchNormalized Mean Square ErrorConvolutional neural network (CNN)-based methodsDeep learning-based denoisersConditional generative adversarial networkKernel’s receptive fieldLearning-based denoisingGenerative adversarial networkProjection-domainReceptive fieldsMean square errorList mode dataDenoising performanceAttention schemeAdversarial networkConvolution kernelAdam optimizerPerfusion defect sizeDenoisingNormalized standard deviationFull doseCGANMP-SPECTDose levelsLow dosesSquare errork-SALSA: k-Anonymous Synthetic Averaging of Retinal Images via Local Style Alignment
Jeon M, Park H, Kim H, Morley M, Cho H. k-SALSA: k-Anonymous Synthetic Averaging of Retinal Images via Local Style Alignment. Lecture Notes In Computer Science 2022, 13681: 661-678. PMID: 37525827, PMCID: PMC10388376, DOI: 10.1007/978-3-031-19803-8_39.Peer-Reviewed Original ResearchStyle alignmentMembership inference attacksRetinal imagesGenerative adversarial networkPotential of machineRetinal image analysisRetinal fundus imagesK-anonymityInference attacksPrivacy notionPrivate datasetAdversarial networkData sharingBenchmark datasetsTraining dataClassification performanceModern machineArt techniquesSource imagesImage fidelityFundus imagesPrior workVisual patternsImage analysisImagesFlow-Based Visual Quality Enhancer for Super-Resolution Magnetic Resonance Spectroscopic Imaging
Dong S, Hangel G, Chen E, Sun S, Bogner W, Widhalm G, You C, Onofrey J, de Graaf R, Duncan J. Flow-Based Visual Quality Enhancer for Super-Resolution Magnetic Resonance Spectroscopic Imaging. Lecture Notes In Computer Science 2022, 13609: 3-13. DOI: 10.1007/978-3-031-18576-2_1.Peer-Reviewed Original ResearchAdversarial networkVisual qualityDeep learning-based super-resolution methodsLearning-based super-resolution methodsFlow-based modelImage visual qualityGenerative adversarial networkHigh visual qualitySuper-resolution methodSuper-resolved imagesGenerative modelHigh-resolution imagesImage modalitiesFlow-based methodNetworkLow spatial resolutionUncertainty estimationImagesPromising resultsEnhancer networkAnatomical informationHigh fidelityEssential toolDatasetQuality adjustmentDeep learning-based denoising in projection-domain and reconstruction-domain for low-dose myocardial perfusion SPECT
Sun J, Jiang H, Du Y, Li C, Wu T, Liu Y, Yang B, Mok G. Deep learning-based denoising in projection-domain and reconstruction-domain for low-dose myocardial perfusion SPECT. Journal Of Nuclear Cardiology 2022, 30: 970-985. PMID: 35982208, DOI: 10.1007/s12350-022-03045-x.Peer-Reviewed Original ResearchConceptsConditional generative adversarial networkGenerative adversarial networkImage qualityAdversarial networkOS-EM methodList-mode dataXCAT phantomPost-reconstruction filteringImagesSPECT projectionsDenoisingMyocardial perfusion SPECTHigh noise levelsPerfusion SPECTFull doseSPECT/CT scansNetworkDifferent anatomical variationsMode dataFilteringMP-SPECTLD imagesSOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks
Zhang K, Hu H, Philbrick K, Conte G, Sobek J, Rouzrokh P, Erickson B. SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks. Tomography 2022, 8: 905-919. PMID: 35448707, PMCID: PMC9027099, DOI: 10.3390/tomography8020073.Peer-Reviewed Original ResearchConceptsSingle-image super-resolutionMedical imagesPixel-wise loss functionsHigh-dimensional feature spaceGenerative adversarial networkImage-based tasksSR worksHR imagesPerceptual lossTexture detailsAdversarial networkFeature spaceSuper-ResolutionDeep learningSemantic distanceLoss functionApparent spatial resolutionResolution-enhancement methodsImage qualityInterpolation techniqueMotion-induced artifactsNetworkHigh-resolutionImagesResearch applications
2021
A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET
Xue S, Guo R, Bohn K, Matzke J, Viscione M, Alberts I, Meng H, Sun C, Zhang M, Zhang M, Sznitman R, El Fakhri G, Rominger A, Li B, Shi K. A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET. European Journal Of Nuclear Medicine And Molecular Imaging 2021, 49: 1843-1856. PMID: 34950968, PMCID: PMC9015984, DOI: 10.1007/s00259-021-05644-1.Peer-Reviewed Original ResearchConceptsStructural similarity index measurePET imagingGenerative adversarial networkNuclear medicine physiciansArtificial intelligenceLow-dose scansBaseline image qualityDose reductionConditional generative adversarial networkClinical imaging assessmentSimilarity index measureDiversity of clinical practiceDevelopment of AI technologyDeep learning developmentDose acquisitionImaging assessmentMedicine physiciansImage qualityResultsThe improvementPatientsClinical acceptanceClinical practiceClinical settingAdversarial networkLow-dose PETSimultaneous deep generative modelling and clustering of single-cell genomic data
Liu Q, Chen S, Jiang R, Wong W. Simultaneous deep generative modelling and clustering of single-cell genomic data. Nature Machine Intelligence 2021, 3: 536-544. PMID: 34179690, PMCID: PMC8223760, DOI: 10.1038/s42256-021-00333-y.Peer-Reviewed Original ResearchSingle-cell genomic dataSingle-cell ATAC-seqScATAC-seq dataChromatin accessibility landscapeSingle cell dataIntegrated analysisSingle-cell technologiesDeep generative neural networksLarge-scale profilingGenerative neural networkATAC-seqScATAC-seqGenerative adversarial networkSingle-cell levelGenomic dataDeep generative modelsState of cellsBiological cell typesAccessibility landscapeLatent representationAdversarial networkLatent featuresNeural networkCell typesDownstream applicationsDirect Image-Based Attenuation Correction using Conditional Generative Adversarial Network for SPECT Myocardial Perfusion Imaging.
Torkaman M, Yang J, Shi L, Wang R, Miller EJ, Sinusas AJ, Liu C, Gullberg GT, Seo Y. Direct Image-Based Attenuation Correction using Conditional Generative Adversarial Network for SPECT Myocardial Perfusion Imaging. Proceedings Of SPIE--the International Society For Optical Engineering 2021, 11600: 27. PMID: 33727759, PMCID: PMC7956874, DOI: 10.1117/12.2580922.Peer-Reviewed Original Research
2020
Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-scale Generative Adversarial Network
Cui J, Gong K, Han P, Liu H, Li Q. Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-scale Generative Adversarial Network. Lecture Notes In Computer Science 2020, 12436: 50-59. DOI: 10.1007/978-3-030-59861-7_6.Peer-Reviewed Original ResearchPeak signal-to-noise ratioGenerative adversarial networkStructural similarity indexMulti-scale generative adversarial networkSignal-to-noise ratioSuper-ResolutionAdversarial networkHigher peak signal-to-noise ratioLow resolutionSuper-resolution methodsLow signal-to-noise ratioUnsupervised trainingPre-trainingWhole tissue volumeNoise interferenceGround truthSpline interpolation methodSimilarity indexConventional ASLNetworkImage noiseInterpolation methodLong acquisition timesHigh-resolutionStructural information
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