2024
Mine yOur owN Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels
You C, Dai W, Liu F, Min Y, Dvornek N, Li X, Clifton D, Staib L, Duncan J. Mine yOur owN Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels. IEEE Transactions On Pattern Analysis And Machine Intelligence 2024, 46: 11136-11151. PMID: 39269798, DOI: 10.1109/tpami.2024.3461321.Peer-Reviewed Original ResearchMedical image segmentationImage segmentationMedical image segmentation frameworkContext of medical image segmentationLong-tailed class distributionStrong data augmentationsIntra-class variationsSemi-supervised settingData imbalance issueImage segmentation frameworkMedical image analysisMedical image dataSupervision signalsContrastive learningBenchmark datasetsUnsupervised mannerLabel setsData augmentationSegmentation frameworkDomain expertisePseudo-codeImbalance issueModel trainingMedical imagesSegmentation model
2020
Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content Space
Yang J, Li X, Pak D, Dvornek N, Chapiro J, Lin M, Duncan J. Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content Space. Lecture Notes In Computer Science 2020, 12444: 52-61. DOI: 10.1007/978-3-030-60548-3_6.Peer-Reviewed Original ResearchSemantic alignmentDomain shiftContent spaceCross-modality medical image segmentationUnsupervised domain adaptation problemMedical image tasksMedical image segmentationDeep convolutional networksDomain adaptation problemAdversarial training strategyAdvantage of imagesQualitative experimental resultsDifferent modalitiesDeep networkPretext taskConvolutional networkSegmentation taskImage segmentationImage tasksSegmentation performanceArt performanceLiver segmentationModality alignmentGeneralization abilitySegmentation pipeline