Deep-Learning-Based Automated Rotator Cuff Tear Screening in Three Planes of Shoulder MRI

This study aimed to develop a screening model for rotator cuff tear detection in all three planes of routine shoulder MRI using a deep neural network. A total of 794 shoulder MRI scans (374 men and 420 women; aged 59 ± 11 years) were utilized. Three musculoskeletal radiologists labeled the rotator c...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Kyu-Chong, Cho, Yongwon, Ahn, Kyung-Sik, Park, Hyun-Joon, Kang, Young-Shin, Lee, Sungshin, Kim, Dongmin, Kang, Chang Ho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606560/
https://www.ncbi.nlm.nih.gov/pubmed/37892075
http://dx.doi.org/10.3390/diagnostics13203254

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606560/
https://www.ncbi.nlm.nih.gov/pubmed/37892075
http://dx.doi.org/10.3390/diagnostics13203254

Ejemplares similares