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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Vydané v:	Frontiers in neurology Ročník 14; s. 1105276
Hlavní autori:	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
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland Frontiers Media S.A 24.02.2023
Predmet:	FSHD machine learning muscle MRI Neurology radiomics stir FSHD radiomics muscle MRI machine learning stir
ISSN:	1664-2295, 1664-2295
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