Evaluation of a Bayesian penalized likelihood reconstruction algorithm for low-count clinical (18)F-FDG PET/CT

BACKGROUND: Recently, a Bayesian penalized likelihood (BPL) reconstruction algorithm was introduced for a commercial PET/CT with the potential to improve image quality. We compared the performance of this BPL algorithm with conventional reconstruction algorithms under realistic clinical conditions s...

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Detalles Bibliográficos
Autores principales: te Riet, Joost, Rijnsdorp, Sjoerd, Roef, Mark J., Arends, Albert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6937357/
https://www.ncbi.nlm.nih.gov/pubmed/31889228
http://dx.doi.org/10.1186/s40658-019-0262-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6937357/
https://www.ncbi.nlm.nih.gov/pubmed/31889228
http://dx.doi.org/10.1186/s40658-019-0262-y

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