| 郑喻文,武玉花,陈晓飞,董馥闻,王平,周晟.深度学习用于肩关节影像学研究进展[J].中国医学影像技术,2024,40(2):302~305 |
| 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 |
| 投稿时间：2023-08-24 修订日期：2023-11-09 |
| DOI：10.13929/j.issn.1003-3289.2024.02.031 |
| 中文关键词: 肩关节 诊断显像 深度学习 |
| 英文关键词:shoulder joint diagnostic imaging deep learning |
| 基金项目:甘肃省自然科学基金（22JR5RA699）。 |
|
| 摘要点击次数: 489 |
| 全文下载次数: 318 |
| 中文摘要: |
| 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。 |
| 英文摘要: |
| 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. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
