A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To utilize a deep learning model for automatic detection of abnormalities in chest CT images from COVID-19 patients and compare its quantitative determination performance with radiological residents.

Authors

  • Qianqian Ni
    Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China.
  • Zhi Yuan Sun
    Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China.
  • Li Qi
    Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, No.305, Zhongshan East Road, Nanjing, 210002, China.
  • Wen Chen
    School of Cyber Science and Engineering, Sichuan University, Chengdu, Sichuan, China.
  • Yi Yang
    Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Xinyuan Zhang
    Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China.
  • Liu Yang
    Department of Ultrasound, Hunan Children's Hospital, Changsha, China.
  • Yi Fang
    Department of Neurosurgery, The Fuzhou General Hospital, Fuzhou, China.
  • Zijian Xing
    Deepwise AI Lab, Beijing, 100080, China.
  • Zhen Zhou
    Deepwise Healthcare, Beijing 100080, China.
  • Yizhou Yu
    Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong.
  • Guang Ming Lu
  • Long Jiang Zhang