Style mixup enhanced disentanglement learning for unsupervised domain adaptation in medical image segmentation
Cai Z, Xin J, You C, Shi P, Dong S, Dvornek N, Zheng N, Duncan J. Style mixup enhanced disentanglement learning for unsupervised domain adaptation in medical image segmentation. Medical Image Analysis 2024, 101: 103440. PMID: 39764933, DOI: 10.1016/j.media.2024.103440.Peer-Reviewed Original ResearchConceptsUnsupervised domain adaptationMedical image segmentationDomain-invariant representationsImage segmentationDomain adaptationDisentanglement learningImage translationUnsupervised domain adaptation approachState-of-the-art methodsDomain shift problemDomain-invariant learningState-of-the-artPublic cardiac datasetsDiverse constraintsAdversarial learningConsistency regularizationContrastive learningFeature spaceSemantic consistencyComprehensive experimentsDomain generalizationData diversityShift problemMedical segmentationCardiac datasetsCascaded 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, 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 results
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