Deep progressive learning achieves whole-body low-dose 18F-FDG PET imaging

Taisong Wang, Wenli Qiao, Ying Wang, Jingyi Wang, Yang Lv, Yun Dong, Zheng Qian, Yan Xing & Jinhua Zhao
Abstract Objectives To validate a total-body PET-guided deep progressive learning reconstruction method (DPR) for low-dose 18F-FDG PET imaging. Methods List-mode data from the retrospective study (n = 26) were rebinned into short-duration scans and reconstructed with DPR. The standard uptake value (SUV) and tumor-to-liver ratio (TLR) in lesions and coefficient of variation (COV) in the liver in the DPR images were compared to the reference (OSEM images with full-duration data). In the prospective study, another...
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