Optimization of a Bayesian penalized likelihood algorithm (Q.Clear) for (18)F-NaF bone PET/CT images acquired over shorter durations using a custom-designed phantom

BACKGROUND: The Bayesian penalized likelihood (BPL) algorithm Q.Clear (GE Healthcare) allows fully convergent iterative reconstruction that results in better image quality and quantitative accuracy, while limiting image noise. The present study aimed to optimize BPL reconstruction parameters for (18...

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Detalhes bibliográficos
Publicado no:EJNMMI Phys
Main Authors: Yoshii, Tokiya, Miwa, Kenta, Yamaguchi, Masashi, Shimada, Kai, Wagatsuma, Kei, Yamao, Tensho, Kamitaka, Yuto, Hiratsuka, Seiya, Kobayashi, Rinya, Ichikawa, Hajime, Miyaji, Noriaki, Miyazaki, Tsuyoshi, Ishii, Kenji
Formato: Artigo
Idioma:Inglês
Publicado em: Springer International Publishing 2020
Assuntos:
Original Research
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7486353/
https://ncbi.nlm.nih.gov/pubmed/32915344
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s40658-020-00325-8
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