Llucia Coll, Deborah Pareto, Pere Carbonell-Mirabent, Álvaro Cobo-Calvo, Georgina Arrambide, Ángela Vidal-Jordana, Manuel Comabella, Joaquín Castilló, Breogán Rodríguez-Acevedo, Ana Zabalza, Ingrid Galán, Luciana Midaglia, Carlos Nos, Annalaura Salerno, Cristina Auger, Manel Alberich, Jordi Río, Jaume Sastre-Garriga, Arnau Oliver, Xavier Montalban, Àlex Rovira, Mar Tintoré, Xavier Lladó, Carmen Tur
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 conventional methods. Additionally, the study of CNN-derived attention maps, which indicate the most relevant anatomical features for CNN-based decisions, has the potential to uncover key disease mechanisms leading to disability accumulation...
March 15, 2023: NeuroImage: Clinical