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
2018
Iterative PET Image Reconstruction Using Convolutional Neural Network Representation
Gong K, Guan J, Kim K, Zhang X, Yang J, Seo Y, Fakhri G, Qi J, Li Q. Iterative PET Image Reconstruction Using Convolutional Neural Network Representation. IEEE Transactions On Medical Imaging 2018, 38: 675-685. PMID: 30222554, PMCID: PMC6472985, DOI: 10.1109/tmi.2018.2869871.Peer-Reviewed Original ResearchConceptsPET image reconstructionNeural networkConvolutional neural network representationsDeep residual convolutional neural networkImage reconstructionResidual convolutional neural networkComputer vision tasksDeep neural networksConvolutional neural networkNeural network denoisersAlternating direction methodNeural network representationIterative reconstruction frameworkNeural network methodVision tasksImage representationNetwork denoisingReconstruction frameworkMultipliers algorithmMedical imagesOptimization problemNetwork methodPost-processing toolDirection methodNetwork representation