Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI

The application of convolutional neural networks (CNNs) to MRI data has emerged as a promising approach to achieving unprecedented levels of accuracy when predicting the course of neurological conditions, including multiple sclerosis, by means of extracting image features not detectable through conv...

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Detalles Bibliográficos
Autores principales: Coll, Llucia, Pareto, Deborah, Carbonell-Mirabent, Pere, Cobo-Calvo, Álvaro, Arrambide, Georgina, Vidal-Jordana, Ángela, Comabella, Manuel, Castilló, Joaquín, Rodríguez-Acevedo, Breogán, Zabalza, Ana, Galán, Ingrid, Midaglia, Luciana, Nos, Carlos, Salerno, Annalaura, Auger, Cristina, Alberich, Manel, Río, Jordi, Sastre-Garriga, Jaume, Oliver, Arnau, Montalban, Xavier, Rovira, Àlex, Tintoré, Mar, Lladó, Xavier, Tur, Carmen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034138/
https://www.ncbi.nlm.nih.gov/pubmed/36940621
http://dx.doi.org/10.1016/j.nicl.2023.103376

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034138/
https://www.ncbi.nlm.nih.gov/pubmed/36940621
http://dx.doi.org/10.1016/j.nicl.2023.103376

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