2024
Cross noise level PET denoising with continuous adversarial domain generalization
Liu X, Eslahi S, Marin T, Tiss A, Chemli Y, Huang Y, Johnson K, Fakhri G, Ouyang J. Cross noise level PET denoising with continuous adversarial domain generalization. Physics In Medicine And Biology 2024, 69: 085001. PMID: 38484401, PMCID: PMC11195012, DOI: 10.1088/1361-6560/ad341a.Peer-Reviewed Original ResearchDomain generalization techniqueDomain generalizationDenoising performanceSuperior denoising performanceLatent feature representationGeneral techniqueDistribution shiftsAdversarial trainingDenoised imageFeature representationDomain labelsDistribution divergenceNoise levelDeep learningImage spaceDenoisingPerformance degradationCore ideaNoise realizationsCD methodNoiseImage volumesPerformanceImagesPSNR
2022
Low-Dose Tau PET Imaging Based on Swin Restormer with Diagonally Scaled Self-Attention
Jang S, Lois C, Becker J, Thibault E, Li Y, Price J, Fakhri G, Li Q, Johnson K, Gong K. Low-Dose Tau PET Imaging Based on Swin Restormer with Diagonally Scaled Self-Attention. 2022, 00: 1-3. DOI: 10.1109/nss/mic44845.2022.10399169.Peer-Reviewed Original ResearchConvolutional neural networkSelf-attention mechanismSelf-attentionTransformer architectureComputer vision tasksLocal feature extractionLong-range informationVision tasksDenoising performanceSwin TransformerFeature extractionImage datasetsUNet structureNeural networkSwinComputational costReceptive fieldsImage qualityMap calculationNetwork structureArchitecturePET image qualityChannel dimensionsQuantitative evaluationDenoising