Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets

OBJECTIVES: This study aimed at developing a convolutional neural network (CNN) able to automatically quantify and characterize the level of degeneration of rotator cuff (RC) muscles from shoulder CT images including muscle atrophy and fatty infiltration. METHODS: One hundred three shoulder CT scans...

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Detalles Bibliográficos
Autores principales: Taghizadeh, Elham, Truffer, Oskar, Becce, Fabio, Eminian, Sylvain, Gidoin, Stacey, Terrier, Alexandre, Farron, Alain, Büchler, Philippe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Musculoskeletal
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755645/
https://www.ncbi.nlm.nih.gov/pubmed/32696257
http://dx.doi.org/10.1007/s00330-020-07070-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755645/
https://www.ncbi.nlm.nih.gov/pubmed/32696257
http://dx.doi.org/10.1007/s00330-020-07070-7

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