A deep learning-based whole-body solution for PET/MRI attenuation correction

BACKGROUND: Deep convolutional neural networks have demonstrated robust and reliable PET attenuation correction (AC) as an alternative to conventional AC methods in integrated PET/MRI systems. However, its whole-body implementation is still challenging due to anatomical variations and the limited MR...

Descripción completa

Detalles Bibliográficos
Autores principales: Ahangari, Sahar, Beck Olin, Anders, Kinggård Federspiel, Marianne, Jakoby, Bjoern, Andersen, Thomas Lund, Hansen, Adam Espe, Fischer, Barbara Malene, Littrup Andersen, Flemming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9385907/
https://www.ncbi.nlm.nih.gov/pubmed/35978211
http://dx.doi.org/10.1186/s40658-022-00486-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9385907/
https://www.ncbi.nlm.nih.gov/pubmed/35978211
http://dx.doi.org/10.1186/s40658-022-00486-8

Ejemplares similares