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A multi-centric evaluation of self-learning GAN based pseudo-CT generation software for low field pelvic magnetic resonance imaging
PURPOSE/OBJECTIVES: An 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 METHOD: In collaboration with TheraPanacea (TheraPanacea, Paris, France)...
Autores principales: | Prunaretty, Jessica, Güngör, Gorkem, Gevaert, Thierry, Azria, David, Valdenaire, Simon, Balermpas, Panagiotis, Boldrini, Luca, Chuong, Michael David, De Ridder, Mark, Hardy, Leo, Kandiban, Sanmady, Maingon, Philippe, Mittauer, Kathryn Elizabeth, Ozyar, Enis, Roque, Thais, Colombo, Lorenzo, Paragios, Nikos, Pennell, Ryan, Placidi, Lorenzo, Shreshtha, Kumar, Speiser, M. P., Tanadini-Lang, Stephanie, Valentini, Vincenzo, Fenoglietto, Pascal |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667706/ https://www.ncbi.nlm.nih.gov/pubmed/38023165 http://dx.doi.org/10.3389/fonc.2023.1245054 |
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