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