Evaluating a radiotherapy deep learning synthetic CT algorithm for PET-MR attenuation correction in the pelvis

Evaluating a radiotherapy deep learning synthetic CT algorithm for PET-MR attenuation correction in the pelvis

Abstract Background Positron emission tomography–magnetic resonance (PET-MR) attenuation correction is challenging because the MR signal does not represent tissue density and conventional MR sequences cannot image bone. A novel zero echo time (ZTE) MR sequence has been previously developed which gen...

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Bibliographic Details
Main Authors: Jonathan J. Wyatt, Sandeep Kaushik, Cristina Cozzini, Rachel A. Pearson, George Petrides, Florian Wiesinger, Hazel M. McCallum, Ross J. Maxwell
Format: Article
Language:English
Published: SpringerOpen 2024-01-01
Series:EJNMMI Physics
Subjects:
Synthetic CT
PET-MR
Attenuation correction
Radiotherapy
Online Access:https://doi.org/10.1186/s40658-024-00617-3

Internet

https://doi.org/10.1186/s40658-024-00617-3

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