Radiomics and machine learning applied to STIR sequence for prediction of quantitative parameters in facioscapulohumeral disease

Quantitative Muscle MRI (qMRI) is a valuable and non-invasive tool to assess disease involvement and progression in neuromuscular disorders being able to detect even subtle changes in muscle pathology. The aim of this study is to evaluate the feasibility of using a conventional short-tau inversion r...

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Bibliographic Details

Published in:	Frontiers in neurology Vol. 14; p. 1105276
Main Authors:	Colelli, Giulia, Barzaghi, Leonardo, Paoletti, Matteo, Monforte, Mauro, Bergsland, Niels, Manco, Giulia, Deligianni, Xeni, Santini, Francesco, Ricci, Enzo, Tasca, Giorgio, Mira, Antonietta, Figini, Silvia, Pichiecchio, Anna
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Media S.A 24.02.2023
Subjects:	FSHD machine learning muscle MRI Neurology radiomics stir FSHD radiomics muscle MRI machine learning stir
ISSN:	1664-2295, 1664-2295
Online Access:	Get full text
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