Convolutional neural networks for PET functional volume fully automatic segmentation: development and validation in a multi-center setting

PURPOSE: In this work, we addressed fully automatic determination of tumor functional uptake from positron emission tomography (PET) images without relying on other image modalities or additional prior constraints, in the context of multicenter images with heterogeneous characteristics. METHODS: In...

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Detalles Bibliográficos
Autores principales: Iantsen, Andrei, Ferreira, Marta, Lucia, Francois, Jaouen, Vincent, Reinhold, Caroline, Bonaffini, Pietro, Alfieri, Joanne, Rovira, Ramon, Masson, Ingrid, Robin, Philippe, Mervoyer, Augustin, Rousseau, Caroline, Kridelka, Frédéric, Decuypere, Marjolein, Lovinfosse, Pierre, Pradier, Olivier, Hustinx, Roland, Schick, Ulrike, Visvikis, Dimitris, Hatt, Mathieu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440243/
https://www.ncbi.nlm.nih.gov/pubmed/33772335
http://dx.doi.org/10.1007/s00259-021-05244-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8440243/
https://www.ncbi.nlm.nih.gov/pubmed/33772335
http://dx.doi.org/10.1007/s00259-021-05244-z

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