Feasibility of automatic measurements of hip joints based on pelvic radiography and a deep learning algorithm.

Abstract

Authors

• Wei Yang
  Key Laboratory of Structure-Based Drug Design and Discovery (Shenyang Pharmaceutical University), Ministry of Education, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Wenhua Road 103, Shenyang 110016, PR China. Electronic address: 421063202@qq.com.
• Qin Ye
  Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.
• Shuai Ming
  Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, 310013, China.
• Xingfei Hu
  Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou 310014, China. Electronic address: 1968724343@qq.com.
• Zhiqiang Jiang
  Hangzhou Jianpei Technology Co., Ltd, Hangzhou, China.
• Qiang Shen
  Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
• Linyang He
  Hangzhou Jianpei Technology Co., Ltd, Hangzhou, China.
• Xiangyang Gong
  Rehabilitation Medicine Center, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.; Institute of Artificial Intelligence and Remote Imaging, Hangzhou Medical College, Hangzhou 310014, China. Electronic address: gong.xy@vip.163.com.

Keywords

External Resources