2023
Incremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI
Liu X, Shih H, Xing F, Santarnecchi E, El Fakhri G, Woo J. Incremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI. Lecture Notes In Computer Science 2023, 14221: 46-56. PMID: 38665992, PMCID: PMC11045038, DOI: 10.1007/978-3-031-43895-0_5.Peer-Reviewed Original ResearchDeep learningDL modelsBrain tumor segmentation taskAbsence of training dataIncremental learning settingSegmenting various anatomical structuresBig medical dataInitial model trainingTumor segmentation taskBatch renormalizationCatastrophic forgettingIncremental learningSegmentation taskSource domainTraining dataModel trainingLearning structureSegmentation modelNetwork optimizationDiverse datasetsMedical dataEvolving environmentLearning settingsDistribution shiftsIncremental structure
2022
Unsupervised Black-Box Model Domain Adaptation for Brain Tumor Segmentation
Liu X, Yoo C, Xing F, Kuo C, Fakhri G, Kang J, Woo J. Unsupervised Black-Box Model Domain Adaptation for Brain Tumor Segmentation. Frontiers In Neuroscience 2022, 16: 837646. PMID: 35720708, PMCID: PMC9201342, DOI: 10.3389/fnins.2022.837646.Peer-Reviewed Original ResearchUnsupervised domain adaptationDomain adaptationSource domainTarget domainLabeled source domain to unlabeled target domainTransfer of domain knowledgeTarget-specific representationsUnlabeled target domainTarget domain dataKnowledge distillation schemeDeep learning backbonesEntropy minimizationTrained model parametersDifficulty of labelingDomain knowledgeSensitive informationPrivacy concernsPerformance gainsNetwork parametersSegmentation modelDomain dataSource dataCross-center collaborationDistillation schemePotential leaksUnsupervised domain adaptation for segmentation with black-box source model
Liu X, Yoo C, Xing F, Kuo C, El Fakhri G, Kang J, Woo J. Unsupervised domain adaptation for segmentation with black-box source model. Proceedings Of SPIE--the International Society For Optical Engineering 2022, 12032: 1203210-1203210-6. PMID: 35983176, PMCID: PMC9385170, DOI: 10.1117/12.2607895.Peer-Reviewed Original ResearchUnsupervised domain adaptationSource domainDomain adaptationTarget-specific representationsLabeled source domainUnlabeled target domainTarget domain dataWell-labeled dataKnowledge distillation schemeTrained model parametersModel adaptation approachOriginal source dataDifficulty of labelingTarget domainSegmentation modelDomain dataTransfer knowledgeEntropy minimizationAdaptive approachSource dataConventional solutionsPractical solutionDistillation schemePrivacyLarge-scale