Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning

BACKGROUND: Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is time-consuming. Previously, deep learning methods have been developed that can either non-invasively predict the genetic or hist...

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Detalles Bibliográficos
Autores principales: van der Voort, Sebastian R, Incekara, Fatih, Wijnenga, Maarten M J, Kapsas, Georgios, Gahrmann, Renske, Schouten, Joost W, Nandoe Tewarie, Rishi, Lycklama, Geert J, De Witt Hamer, Philip C, Eijgelaar, Roelant S, French, Pim J, Dubbink, Hendrikus J, Vincent, Arnaud J P E, Niessen, Wiro J, van den Bent, Martin J, Smits, Marion, Klein, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Basic and Translational Investigations
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925710/
https://www.ncbi.nlm.nih.gov/pubmed/35788352
http://dx.doi.org/10.1093/neuonc/noac166

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925710/
https://www.ncbi.nlm.nih.gov/pubmed/35788352
http://dx.doi.org/10.1093/neuonc/noac166

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