Quality control of elbow joint radiography using a YOLOv8-based artificial intelligence technology.

Journal: European radiology experimental
PMID:

Abstract

BACKGROUND: To explore an artificial intelligence (AI) technology employing YOLOv8 for quality control (QC) on elbow joint radiographs.

Authors

  • Qi Lai
    Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Yuzhong, Chongqing, China.
  • Weijuan Chen
    Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, No. 74 Linjiang Rd, Yuzhong District, Chongqing, 400010, China.
  • Xuan Ding
    Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Yuzhong, Chongqing, China.
  • Xin Huang
    Department of ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
  • Wenli Jiang
    Department of Ultrasound, the First Medical Centre, Chinese PLA General Hospital, Beijing, China.
  • Lingjing Zhang
    Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Yuzhong, Chongqing, China.
  • Jinhua Chen
    Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Yuzhong District, 400010 Chongqing, China. Electronic address: 13908391746@163.com.
  • Dajing Guo
    Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, No. 74 Linjiang Rd, Yuzhong District, Chongqing, 400010, China. guodaj@hospital.cqmu.edu.cn.
  • Zhiming Zhou
    Department of Neurology, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital, Wuhu, China.
  • Tian-Wu Chen
    Department of Radiology, The Second Affiliated Hospital of Chongqing Medical University, Yuzhong, Chongqing, China. tianwuchen_nsmc@163.com.