Deep learning-based automatic scoring models for the disease activity of rheumatoid arthritis based on multimodal ultrasound images.

Journal: Rheumatology (Oxford, England)
Published Date:

Abstract

OBJECTIVES: We aimed to investigate the value of deep learning (DL) models based on multimodal ultrasonographic (US) images to quantify RA activity.

Authors

  • Xuelei He
  • Ming Wang
    Brain center, Zhejiang Hospital, Hangzhou, China.
  • Chenyang Zhao
    SILC Business School, Shanghai University, Shanghai 201800, China.
  • Qian Wang
    Department of Radiation Oncology, China-Japan Union Hospital of Jilin University, Changchun, China.
  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Jian Liu
    Department of Rheumatology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, China.
  • Yixiu Zhang
    Department of Ultrasound, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
  • Zhenhong Qi
    Health Management Center, Foshan Hospital of Traditional Chinese Medicine, Foshan, Guangdong, China.
  • Na Su
    Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Yao Wei
    Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel, Switzerland.
  • Yang Gui
    Department of Ultrasound, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
  • Jianchu Li
    Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China.
  • Xinping Tian
    Department of Rheumatology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
  • Xiaofeng Zeng
    Department of Rheumatology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
  • Yuxin Jiang
    Department of Ultrasound, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, China.
  • Kun Wang
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Meng Yang