A multi-centric evaluation of self-learning GAN based pseudo-CT generation software for low field pelvic magnetic resonance imaging

A multi-centric evaluation of self-learning GAN based pseudo-CT generation software for low field pelvic magnetic resonance imaging

Purpose/objectivesAn artificial intelligence-based pseudo-CT from low-field MR images is proposed and clinically evaluated to unlock the full potential of MRI-guided adaptive radiotherapy for pelvic cancer care.Materials and methodIn collaboration with TheraPanacea (TheraPanacea, Paris, France) a ps...

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Bibliographic Details
Main Authors: Jessica Prunaretty, Gorkem Güngör, Thierry Gevaert, David Azria, Simon Valdenaire, Panagiotis Balermpas, Luca Boldrini, Michael David Chuong, Mark De Ridder, Leo Hardy, Sanmady Kandiban, Philippe Maingon, Kathryn Elizabeth Mittauer, Enis Ozyar, Thais Roque, Lorenzo Colombo, Nikos Paragios, Ryan Pennell, Lorenzo Placidi, Kumar Shreshtha, M. P. Speiser, Stephanie Tanadini-Lang, Vincenzo Valentini, Pascal Fenoglietto
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-11-01
Series:Frontiers in Oncology
Subjects:
pseudo-CT
artificial intelligence
MRI
pelvis
cycle GAN
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2023.1245054/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2023.1245054/full

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