Preliminary exploration of deep learning-assisted recognition of superior labrum anterior and posterior lesions in shoulder MR arthrography.

Journal: International orthopaedics
PMID: 37726561

Abstract

PURPOSE: MR arthrography (MRA) is the most accurate method for preoperatively diagnosing superior labrum anterior-posterior (SLAP) lesions, but diagnostic results can vary considerably due to factors such as experience. In this study, deep learning was used to facilitate the preliminary identification of SLAP lesions and compared with radiologists of different seniority.

Authors

  • Ming Ni
    Department of Orthopaedics, Chinese People's Liberation Army General Hospital (301 Hospital), 28 Fuxing Rd, 100853, Beijing, China.
  • Lixiang Gao
    Department of Radiology, Peking University Third Hospital, 49 Huayuan North Road, Haidian District, Beijing, People's Republic of China.
  • Wen Chen
    School of Cyber Science and Engineering, Sichuan University, Chengdu, Sichuan, China.
  • Qiang Zhao
    Key Laboratory for Organic Electronics and Information Displays (KLOEID) & Jiangsu Key Laboratory for Biosensors, Institute of Advanced Materials (IAM), National Synergetic Innovation Center for Advanced Materials (SICAM), Nanjing University of Posts and Telecommunications, 9 Wenyuan Road, Nanjing 210023, China.
  • Yuqing Zhao
    Faculty of Mechanical and Electrical Engineering, Yunnan Agricultural University, Kunming, Yunnan 650201, PR China. Electronic address: kmyuqing@163.com.
  • Chenyu Jiang
    Department of Radiology, Peking University Third Hospital, 49 Huayuan North Road, Haidian District, Beijing, People's Republic of China.
  • Huishu Yuan
    Department of Radiology, Peking University Third Hospital, Beijing 10019, China.

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