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

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

Abstract 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 li...

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Bibliographic Details
Main Authors: Sahar Ahangari, Anders Beck Olin, Marianne Kinggård Federspiel, Bjoern Jakoby, Thomas Lund Andersen, Adam Espe Hansen, Barbara Malene Fischer, Flemming Littrup Andersen
Format: Article
Language:English
Published: SpringerOpen 2022-08-01
Series:EJNMMI Physics
Subjects:
PET/MRI
MR-AC
Attenuation correction
Deep learning
Whole body
Online Access:https://doi.org/10.1186/s40658-022-00486-8

Internet

https://doi.org/10.1186/s40658-022-00486-8

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