Featured Publications
Attentive 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 ResearchMeSH KeywordsAnisotropyBayes TheoremHumansImage Processing, Computer-AssistedLearningReproducibility of ResultsUncertaintyConceptsUnsupervised 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 scheme
2022
Brain MR Atlas Construction Using Symmetric Deep Neural Inpainting
Xing F, Liu X, Kuo C, Fakhri G, Woo J. Brain MR Atlas Construction Using Symmetric Deep Neural Inpainting. IEEE Journal Of Biomedical And Health Informatics 2022, 26: 3185-3196. PMID: 35139030, PMCID: PMC9250592, DOI: 10.1109/jbhi.2022.3149754.Peer-Reviewed Original ResearchConceptsImage inpainting methodInpainting methodDeep learning-based image inpainting methodsBrain Tumor Segmentation ChallengeMultimodal Brain Tumor Segmentation ChallengeReduce reconstruction errorAtlas constructionStatistical brain atlasInpainted regionsInpainted dataImage registration methodReconstruction errorTumor regionMutual informationSimilarity scoresSegmentation ChallengeSymmetry constraintsImage dataRegistration methodMagnetic resonance imagingTumor locationStatistical atlasDistribution of lesionsCross-correlationPatient population
2021
Segmentation of Cardiac Structures via Successive Subspace Learning with Saab Transform from Cine MRI
Liu X, Xing F, Gaggin H, Wang W, Kuo C, Fakhri G, Woo J. Segmentation of Cardiac Structures via Successive Subspace Learning with Saab Transform from Cine MRI. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2021, 00: 3535-3538. PMID: 34892002, DOI: 10.1109/embc46164.2021.9629770.Peer-Reviewed Original ResearchMeSH KeywordsHeartHeart VentriclesImage Processing, Computer-AssistedMagnetic Resonance Imaging, CineNeural Networks, ComputerConceptsConvolutional neural networkSegmentation of cardiac structuresSaab transformSubspace approximationAccurate segmentation of cardiac structuresDimension reductionConvolutional neural network modelConcatenation of featuresUnsupervised dimension reductionConditional random fieldPixel-wise classificationSupervised dimension reductionU-Net modelMachine learning modelsSubspace learningChannel-wiseSegmentation databaseSegmentation frameworkNeural networkU-NetEfficient segmentationAccurate segmentationLearning modelsCardiac MR imagesRandom field