Performance evaluation of the Q.Clear reconstruction framework versus conventional reconstruction algorithms for quantitative brain PET-MR studies

BACKGROUND: Q.Clear is a Bayesian penalized likelihood (BPL) reconstruction algorithm that presents improvements in signal-to-noise ratio (SNR) in clinical positron emission tomography (PET) scans. Brain studies in research require a reconstruction that provides a good spatial resolution and accentu...

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Detalles Bibliográficos
Autores principales: Ribeiro, Daniela, Hallett, William, Tavares, Adriana A. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8105485/
https://www.ncbi.nlm.nih.gov/pubmed/33961164
http://dx.doi.org/10.1186/s40658-021-00386-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8105485/
https://www.ncbi.nlm.nih.gov/pubmed/33961164
http://dx.doi.org/10.1186/s40658-021-00386-3

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