Assessing the impact of different penalty factors of the Bayesian reconstruction algorithm Q.Clear on in vivo low count kinetic analysis of [(11)C]PHNO brain PET-MR studies

INTRODUCTION: Q.Clear is a Bayesian penalised likelihood (BPL) reconstruction algorithm available on General Electric (GE) Positron Emission Tomography (PET)-Computed Tomography (CT) and PET-Magnetic Resonance (MR) scanners. This algorithm is regulated by a β value which acts as a noise penalisation...

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Detalles Bibliográficos
Autores principales: Ribeiro, Daniela, Hallett, William, Howes, Oliver, McCutcheon, Robert, Nour, Matthew M., Tavares, Adriana A. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8859021/
https://www.ncbi.nlm.nih.gov/pubmed/35184229
http://dx.doi.org/10.1186/s13550-022-00883-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8859021/
https://www.ncbi.nlm.nih.gov/pubmed/35184229
http://dx.doi.org/10.1186/s13550-022-00883-1

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