Magnetic resonance shoulder imaging using deep learning-based algorithm.

Journal: European radiology
Published Date: Feb 24, 2023

Abstract

OBJECTIVE: To investigate the feasibility of deep learning-based MRI (DL-MRI) in its application in shoulder imaging and compare its performance with conventional MR imaging (non-DL-MRI).

Authors

  • Jing Liu
    Department of Ophthalmology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Wei Li
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Ziyuan Li
    Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China.
  • Junzhe Yang
    Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China.
  • Ke Wang
    China Electric Power Research Institute, Haidian District, Beijing 100192, China. wangke1@epri.sgcc.com.cn.
  • Xinming Cao
    Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China.
  • Naishan Qin
    Beijing Smart Tree Medical Technology co. Ltd., Beijing, China.
  • Ke Xue
    Department of Dermatology, China-Japan Friendship Hospital, Beijing 100029, China.
  • Yongming Dai
    Central Research Institute, United Imaging Healthcare, 2258 Chengbei Rd., Jiading District, Shanghai, 201807, China.
  • Peng Wu
    Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Jianxing Qiu
    Department of Radiology, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034, China. qjx761225@126.com.

Keywords

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