2024
Point-supervised Brain Tumor Segmentation with Box-prompted Medical Segment Anything Model
Liu X, Woo J, Ma C, Ouyang J, Fakhri G. Point-supervised Brain Tumor Segmentation with Box-prompted Medical Segment Anything Model. 2011 IEEE Nuclear Science Symposium Conference Record 2024, 00: 1-1. PMID: 39445308, PMCID: PMC11497479, DOI: 10.1109/nss/mic/rtsd57108.2024.10656071.Peer-Reviewed Original Research
2022
Memory consistent unsupervised off-the-shelf model adaptation for source-relaxed medical image segmentation
Liu X, Xing F, El Fakhri G, Woo J. Memory consistent unsupervised off-the-shelf model adaptation for source-relaxed medical image segmentation. Medical Image Analysis 2022, 83: 102641. PMID: 36265264, PMCID: PMC10016738, DOI: 10.1016/j.media.2022.102641.Peer-Reviewed Original ResearchConceptsUnsupervised domain adaptationUnsupervised domain adaptation methodsSource domain dataBN statisticsTarget domainLabeled source domain dataDomain dataLabeled source domainSelf-training strategyPatient data privacyHeterogeneous target domainBrain tumor segmentationPseudo-labelsDomain adaptationUnsupervised adaptationData privacySegmentation taskSource domainImage segmentationVital protocolAdaptation frameworkDecay strategyBoost performanceModel adaptationTumor segmentationACT: Semi-supervised Domain-Adaptive Medical Image Segmentation with Asymmetric Co-training
Liu X, Xing F, Shusharina N, Lim R, Jay Kuo C, El Fakhri G, Woo J. ACT: Semi-supervised Domain-Adaptive Medical Image Segmentation with Asymmetric Co-training. Lecture Notes In Computer Science 2022, 13435: 66-76. PMID: 36780245, PMCID: PMC9911133, DOI: 10.1007/978-3-031-16443-9_7.Peer-Reviewed Original ResearchSemi-supervised domain adaptationUnsupervised domain adaptationSemi-supervised learningMedical image segmentationDomain adaptationDomain shiftLabel supervisionTarget domainImage segmentationDomain dataLeverage different knowledgePseudo-label noiseSignificant domain shiftSupervised joint trainingLabeled source domainUnlabeled target dataUnlabeled target domainLabeled target samplesTarget domain dataSource domain dataState-of-the-artMRI segmentation taskSubstantial performance gainsPseudo-labelsLabel noise
2017
HOSVD-Based Multigraph Cuts for Joint Segmentation of Multi-Channel Images
Chowdhury S, Li Q, Fakhri G, Dutta J. HOSVD-Based Multigraph Cuts for Joint Segmentation of Multi-Channel Images. 2017, 00: 1-2. DOI: 10.1109/nssmic.2017.8532828.Peer-Reviewed Original ResearchImage contextMedical imaging contextMulti-channel imagesJoint segmentation approachSingular value decompositionImage segmentationVoxel similarityLesion segmentationSegmentation approachJoint segmentationEffective segmentationValue decompositionMulti-channelImaging of glioblastomaComposite graphMultiple disease typesSingular vectorsDynamic PET imagesLaplacian tensor