Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation
You C, Xiang J, Su K, Zhang X, Dong S, Onofrey J, Staib L, Duncan J. Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation. Lecture Notes In Computer Science 2022, 13573: 3-16. PMID: 37415747, PMCID: PMC10323962, DOI: 10.1007/978-3-031-18523-6_1.Peer-Reviewed Original ResearchIncremental learningMedical image segmentation tasksMulti-site datasetImage segmentation tasksMedical image segmentationProstate MRI SegmentationComputation resourcesMedical datasetsSegmentation taskImage segmentationSegmentation frameworkEmbedding featuresBenchmark datasetsMRI segmentationTraining dataTarget domainLearning approachPractical deploymentDomain-specific expertiseCompetitive performanceDatasetTraining schemePrior workSegmentationSingle modelAtlas-Based Semantic Segmentation of Prostate Zones
Zhang J, Venkataraman R, Staib L, Onofrey J. Atlas-Based Semantic Segmentation of Prostate Zones. Lecture Notes In Computer Science 2022, 13435: 570-579. PMID: 38084296, PMCID: PMC10711803, DOI: 10.1007/978-3-031-16443-9_55.Peer-Reviewed Original ResearchSegmentation resultsSemantic segmentation frameworkSemantic segmentation resultsDice similarity coefficient valuesSemantic segmentationInference stageSegmentation frameworkSegmentation performanceExternal test datasetTest datasetRegion of interestSegmentationAnatomical atlasHyperparametersSimilarity coefficient valuesAnatomical informationGitHubUsersDatasetProstate zonesCodeFrameworkInformation