2024
Cross 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 volumesPerformanceImagesPSNR
2023
Successive Subspace Learning for Cardiac Disease Classification with Two-Phase Deformation Fields from Cine MRI
Liu X, Xing F, Gaggin H, Kuo C, El Fakhri G, Woo J. Successive Subspace Learning for Cardiac Disease Classification with Two-Phase Deformation Fields from Cine MRI. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2023, 00: 1-5. PMID: 38031559, PMCID: PMC10686280, DOI: 10.1109/isbi53787.2023.10230746.Peer-Reviewed Original ResearchTraining samplesCardiovascular disease classificationCNN-based approachDeep learning modelsCardiac disease classificationSubspace learningSSL modelClassification performanceDeep learningCardiac cine magnetic resonance imagingSubspace approximationSupervised regressionLearning modelsAccurate characterization resultsDisease classificationClassificationCardiac atlasLearningDeformation fieldEnd-systolic phaseFrameworkFeedforward designPerformanceTrainingSSLOutlier 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