2024
Ablation Study of Diffusion Model with Transformer Backbone for Low-count PET Denoising
Huang Y, Liu X, Miyazaki T, Omachi S, Fakhri G, Ouyang J. Ablation Study of Diffusion Model with Transformer Backbone for Low-count PET Denoising. 2011 IEEE Nuclear Science Symposium Conference Record 2024, 00: 1-2. PMID: 39445309, PMCID: PMC11497477, DOI: 10.1109/nss/mic/rtsd57108.2024.10655179.Peer-Reviewed Original ResearchIR tasksImage restorationImage super-resolution taskField of image restorationSuper-resolution taskLatent feature spaceConventional UNetDenoising iterationDenoising taskTransformer backboneDenoising autoencoderTexture restorationVision transformerFeature spaceAblation studiesLearning schemeBackbone networkImage generationDenoisingUNetIR modelPSNRSpatial informationAutoencoderTask
2022
Self-Semantic Contour Adaptation for Cross Modality Brain Tumor Segmentation
Liu X, Xing F, Fakhri G, Woo J. Self-Semantic Contour Adaptation for Cross Modality Brain Tumor Segmentation. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2022, 00: 1-5. PMID: 35990931, PMCID: PMC9387767, DOI: 10.1109/isbi52829.2022.9761629.Peer-Reviewed Original ResearchUnsupervised domain adaptationAdaptive networkLow-level edge informationCross-domain alignmentEnhance segmentation performanceMulti-task frameworkCross-modality segmentationSegmentation of brain tumorsAdversarial learningDomain adaptationSemantic segmentationEdge informationSemantic alignmentPrecursor taskSegmentation performanceSpatial informationNetworkSemantic adaptationMagnetic resonance imagingTaskContour adaptationBraTS2018InformationFrameworkAdaptation
2021
Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation
Liu X, Xing F, Yang C, El Fakhri G, Woo J. Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation. Lecture Notes In Computer Science 2021, 12902: 549-559. PMID: 34734216, PMCID: PMC8562716, DOI: 10.1007/978-3-030-87196-3_51.Peer-Reviewed Original ResearchUnsupervised domain adaptationSegmentation taskSource domainTarget domainUnsupervised domain adaptation methodsLabeled source domainSource domain dataUnsupervised learning methodDomain adaptationUDA methodsPrivacy issuesLearning methodsAdaptation frameworkDomain dataData storageTransfer knowledgeBatch statisticsSource dataOptimization objectivesAdaptation stageTaskFrameworkPrivacyDomainBraTSA Unified Conditional Disentanglement Framework For Multimodal Brain Mr Image Translation
Liu X, Xing F, Fakhri G, Woo J. A Unified Conditional Disentanglement Framework For Multimodal Brain Mr Image Translation. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2021, 00: 10-14. PMID: 34567419, PMCID: PMC8460116, DOI: 10.1109/isbi48211.2021.9433897.Peer-Reviewed Original Research