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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Dettagli Bibliografici
Pubblicato in:EJNMMI Phys
Autori principali: 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
Natura: Artigo
Lingua:Inglês
Pubblicazione: Springer International Publishing 2020
Soggetti:
Original Research
Accesso online: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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