Featured Publications
Mutual Information Regularized Feature-Level Frankenstein for Discriminative Recognition.
Liu X, Yang C, You J, Kuo CJ, Kumar BVKV. Mutual Information Regularized Feature-Level Frankenstein for Discriminative Recognition. IEEE Trans Pattern Anal Mach Intell 2022, 44: 5243-5260. PMID: 33945470, DOI: 10.1109/TPAMI.2021.3077397.Peer-Reviewed Original ResearchOrdinal Unsupervised Domain Adaptation With Recursively Conditional Gaussian Imposed Variational Disentanglement.
Liu X, Li S, Ge Y, Ye P, You J, Lu J. Ordinal Unsupervised Domain Adaptation With Recursively Conditional Gaussian Imposed Variational Disentanglement. IEEE Trans Pattern Anal Mach Intell 2022, PP PMID: 35704544, DOI: 10.1109/TPAMI.2022.3183115.Peer-Reviewed Original ResearchSubtype-Aware Dynamic Unsupervised Domain Adaptation
Liu X, Xing F, You J, Lu J, Kuo C, Fakhri G, Woo J. Subtype-Aware Dynamic Unsupervised Domain Adaptation. IEEE Transactions On Neural Networks And Learning Systems 2024, 35: 2820-2834. PMID: 35895653, DOI: 10.1109/tnnls.2022.3192315.Peer-Reviewed Original ResearchTarget domainSource domain to target domainUnsupervised domain adaptationWithin-class compactnessHeart disease dataPseudo-labelsDomain adaptationClass centersLatent spaceCluster centroidsConditional alignmentLabel shiftTransfer knowledgeQueueing frameworkLocal proximityAlternative processing schemesSubtype labelsExperimental resultsProcessing schemeSubtype structureDomainNetVisDADisease dataDomainLabelingAttentive continuous generative self-training for unsupervised domain adaptive medical image translation
Liu X, Prince J, Xing F, Zhuo J, Reese T, Stone M, El Fakhri G, Woo J. Attentive continuous generative self-training for unsupervised domain adaptive medical image translation. Medical Image Analysis 2023, 88: 102851. PMID: 37329854, PMCID: PMC10527936, DOI: 10.1016/j.media.2023.102851.Peer-Reviewed Original ResearchConceptsUnsupervised domain adaptationImage translationProblem of domain shiftSelf-trainingImage modality translationLabeled source domainTarget domain dataSelf-attention schemeAlternating optimization schemeHeterogeneous target domainContinuous value predictionPseudo-labelsDomain adaptationUDA methodsDomain shiftSoftmax probabilitiesSource domainTarget domainVariational BayesBackground regionsTranslation tasksTraining processDomain dataGeneration taskOptimization schemeMemory consistent unsupervised off-the-shelf model adaptation for source-relaxed medical image segmentation
Liu X, Xing F, El Fakhri G, Woo J. Memory consistent unsupervised off-the-shelf model adaptation for source-relaxed medical image segmentation. Medical Image Analysis 2022, 83: 102641. PMID: 36265264, PMCID: PMC10016738, DOI: 10.1016/j.media.2022.102641.Peer-Reviewed Original ResearchConceptsUnsupervised domain adaptationUnsupervised domain adaptation methodsSource domain dataBN statisticsTarget domainLabeled source domain dataDomain dataLabeled source domainSelf-training strategyPatient data privacyHeterogeneous target domainBrain tumor segmentationPseudo-labelsDomain adaptationUnsupervised adaptationData privacySegmentation taskSource domainImage segmentationVital protocolAdaptation frameworkDecay strategyBoost performanceModel adaptationTumor segmentationAssessment of Transcatheter or Surgical Closure of Atrial Septal Defect using Interpretable Deep Keypoint Stadiometry.
Wang J, Xie W, Cheng M, Wu Q, Wang F, Li P, Fan B, Zhang X, Wang B, Liu X. Assessment of Transcatheter or Surgical Closure of Atrial Septal Defect using Interpretable Deep Keypoint Stadiometry. Research (Wash D C) 2022, 2022: 9790653. PMID: 36340508, DOI: 10.34133/2022/9790653.Peer-Reviewed Original Research
2024
Investigating muscle coordination patterns with Granger causality analysis in protrusive motion from tagged and diffusion MRI
Park H, Xing F, Stone M, Kang H, Liu X, Zhuo J, Fels S, Reese T, Wedeen V, Fakhri G, Prince J, Woo J. Investigating muscle coordination patterns with Granger causality analysis in protrusive motion from tagged and diffusion MRI. JASA Express Letters 2024, 4: 095201. PMID: 39240196, PMCID: PMC11384280, DOI: 10.1121/10.0028500.Peer-Reviewed Original ResearchDiffusion Model-Based Posterior Distribution Prediction for Kinetic Parameter Estimation in Dynamic PET
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Diffusion Model-Based Posterior Distribution Prediction for Kinetic Parameter Estimation in Dynamic PET. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635805.Peer-Reviewed Original ResearchPosterior distributions of kinetic parametersDenoising diffusion probabilistic modelHyperphosphorylated tauP-tauDiffusion probabilistic modelAlzheimer's diseaseNeurodegenerative diseasesKinetic parametersPosterior distributionInference efficiencyComputational needsEstimate kinetic parametersProbabilistic modelComputation timeExploring Backdoor Attacks in Off-the-Shelf Unsupervised Domain Adaptation for Securing Cardiac MRI-Based Diagnosis
Liu X, Xing F, Gaggin H, Kuo C, Fakhri G, Woo J. Exploring Backdoor Attacks in Off-the-Shelf Unsupervised Domain Adaptation for Securing Cardiac MRI-Based Diagnosis. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635403.Peer-Reviewed Original ResearchUnsupervised domain adaptationTarget domain modelBackdoor attacksDomain adaptationTraining dataLabeled source domain dataSusceptible to backdoor attacksAccurate pseudo labelsDomain modelSource domain dataPatient data privacyTarget training dataOff-the-shelfPseudo-labelsData privacySource domainMulti-vendorRandom initializationTraining phaseDomain dataDiagnosis modelTarget modelMulti-diseaseAttacksAuxiliary modelGlobal incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021.
GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024 PMID: 38642570, DOI: 10.1016/S0140-6736(24)00757-8.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsGlobal burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021
GBD 2021 Causes of Death Collaborators. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024 PMID: 38648809, DOI: 10.1016/S0140-6736(24)00824-9.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsCross 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 volumesPerformanceImagesPSNRGlobal fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
GBD 2021 Fertility and Forecasting Collaborators. Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024 PMID: 38521087, DOI: 10.1016/S0140-6736(24)00550-6.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsGlobal age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study
GBD 2021 Demographics Collaborators. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024 PMID: 38484753, DOI: 10.1016/S0140-6736(24)00476-8.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsLearn from orientation prior for radiograph super-resolution: Orientation operator transformer.
Huang Y, Miyazaki T, Liu X, Jiang K, Tang Z, Omachi S. Learn from orientation prior for radiograph super-resolution: Orientation operator transformer. Comput Methods Programs Biomed 2024, 245: 108000. PMID: 38237449, DOI: 10.1016/j.cmpb.2023.108000.Peer-Reviewed Original ResearchThe role of 18F-FDG PET in minimizing variability in gross tumor volume delineation of soft tissue sarcomas
Najem E, Marin T, Zhuo Y, Lahoud R, Tian F, Beddok A, Rozenblum L, Xing F, Moteabbed M, Lim R, Liu X, Woo J, Lostetter S, Lamane A, Chen Y, Ma C, El Fakhri G. The role of 18F-FDG PET in minimizing variability in gross tumor volume delineation of soft tissue sarcomas. Radiotherapy And Oncology 2024, 194: 110186. PMID: 38412906, PMCID: PMC11042980, DOI: 10.1016/j.radonc.2024.110186.Peer-Reviewed Original ResearchGross tumor volume delineationGross tumor volumeDice similarity coefficientF-FDG PET imagingSoft tissue sarcomasInter-reader variabilityGTV delineationRadiation therapy treatment planningF-FDGF-FDG PETTherapy treatment planningPerformance level estimationTumor volume delineationTissue sarcomasPET imagingVolume delineationSimultaneous truthHausdorff distanceDice similarity coefficient scoreAccurate gross tumor volumeImaging modality groupsWilcoxon signed-rank testStatistically significant decreaseSigned-rank testTumor volumeDevelopment and validation of deep-learning network for detecting congenital heart disease from multi-view multi-modal transthoracic echocardiograms
Mingmei Cheng, Jing Wang, Xiaofeng Liu, Yanzhong Wang, Qun Wu, Fangyun Wang, Pei Li, Binbin Wang, Xin Zhang, Wanqing xie. Development and validation of deep-learning network for detecting congenital heart disease from multi-view multi-modal transthoracic echocardiograms. Research. 0:DOI:10.34133/research.0319Peer-Reviewed Original Research
2023
Deep learning based lesions detection and severity grading of small bowel Crohn's disease ulcers on double-balloon endoscopy images.
Xie W, Hu J, Liang P, Mei Q, Wang A, Liu Q, Liu X, Wu J, Yang X, Zhu N, Bai B, Mei Y, Liang Z, Han W, Cheng M. Deep learning based lesions detection and severity grading of small bowel Crohn's disease ulcers on double-balloon endoscopy images. Gastrointest Endosc 2023 PMID: 38065509, DOI: 10.1016/j.gie.2023.11.059.Peer-Reviewed Original ResearchSource-free domain adaptive segmentation with class-balanced complementary self-training.
Huang Y, Xie W, Li M, Xiao E, You J, Liu X. Source-free domain adaptive segmentation with class-balanced complementary self-training. Artif Intell Med 2023, 146: 102694. PMID: 38042612, DOI: 10.1016/j.artmed.2023.102694.Peer-Reviewed Original ResearchIncremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI
Liu X, Shih H, Xing F, Santarnecchi E, El Fakhri G, Woo J. Incremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI. Lecture Notes In Computer Science 2023, 14221: 46-56. PMID: 38665992, PMCID: PMC11045038, DOI: 10.1007/978-3-031-43895-0_5.Peer-Reviewed Original ResearchDeep learningDL modelsBrain tumor segmentation taskAbsence of training dataIncremental learning settingSegmenting various anatomical structuresBig medical dataInitial model trainingTumor segmentation taskBatch renormalizationCatastrophic forgettingIncremental learningSegmentation taskSource domainTraining dataModel trainingLearning structureSegmentation modelNetwork optimizationDiverse datasetsMedical dataEvolving environmentLearning settingsDistribution shiftsIncremental structure