A deep learning model to generate synthetic CT for prostate MR-only radiotherapy dose planning: a multicenter study.

Fiche publication

Date publication

novembre 2023

Journal

Frontiers in oncology

Auteurs

Membres identifiés du Cancéropôle Est :
Dr BESSIERES Igor

Tous les auteurs :
Tahri S, Texier B, Nunes JC, Hemon C, Lekieffre P, Collot E, Chourak H, Le Guevelou J, Greer P, Dowling J, Acosta O, Bessieres I, Marage L, Boue-Rafle A, De Crevoisier R, Lafond C, Barateau A

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/38090490

Résumé

For radiotherapy based solely on magnetic resonance imaging (MRI), generating synthetic computed tomography scans (sCT) from MRI is essential for dose calculation. The use of deep learning (DL) methods to generate sCT from MRI has shown encouraging results if the MRI images used for training the deep learning network and the MRI images for sCT generation come from the same MRI device. The objective of this study was to create and evaluate a generic DL model capable of generating sCTs from various MRI devices for prostate radiotherapy.