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

OBJECTIVES: To validate a total-body PET-guided deep progressive learning reconstruction method (DPR) for low-dose (18)F-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)...

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Detalles Bibliográficos
Autores principales: Wang, Taisong, Qiao, Wenli, Wang, Ying, Wang, Jingyi, Lv, Yang, Dong, Yun, Qian, Zheng, Xing, Yan, Zhao, Jinhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681960/
https://www.ncbi.nlm.nih.gov/pubmed/36414772
http://dx.doi.org/10.1186/s40658-022-00508-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681960/
https://www.ncbi.nlm.nih.gov/pubmed/36414772
http://dx.doi.org/10.1186/s40658-022-00508-5

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