深度学习用于肩关节影像学研究进展  

Research progresses of deep learning in shoulder joint imaging

作　　者：郑喻文 武玉花 陈晓飞[2] 董馥闻 王平[3] 周晟 ZHENG Yuwen;WU Yuhua;CHEN Xiaofei;DONG Fuwen;WANG Ping;ZHOU Sheng(The First Clinical Medical School of Gansu University of Chinese Medicine,Lanzhou 730000,China;Department of Radiology,Gansu Provincial Hospital of Traditional Chinese Medicine,Lanzhou 730050,China;Department of Radiology,Gansu Provincial People's Hospital,Lanzhou 730000,China)

机构地区：[1]甘肃中医药大学第一临床医学院,甘肃兰州730000 [2]甘肃省中医院放射科,甘肃兰州730050 [3]甘肃省人民医院放射科,甘肃兰州730000

出　　处：《中国医学影像技术》2024年第2期302-305,共4页Chinese Journal of Medical Imaging Technology

基　　金：甘肃省自然科学基金(22JR5RA699)。

摘　　要：肩痛在肌肉骨骼疼痛中居第三位,人群患病率较高,早期诊断至关重要。深度学习(DL)技术用于肩关节影像学有利于临床诊治肩部疾病及评估预后。本文对DL技术在肩关节影像学中的研究进展进行综述。Shoulder pain ranks the third in musculoskeletal pain,with relatively high incidence in the population.Early diagnosis of shoulder diseases is crucial.Deep learning(DL)in shoulder joint imaging was conducive to clinical diagnosis,treatment and prognosis evaluation of shoulder diseases.The research progresses of DL in shoulder joint imaging were reviewed in this article.

关 键 词：肩关节 诊断显像 深度学习 

分 类 号：R684[医药卫生—骨科学] R445[医药卫生—外科学]