A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19).

Journal: European radiology
Published Date: Feb 24, 2021

Abstract

OBJECTIVE: The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) has caused more than 26 million cases of Corona virus disease (COVID-19) in the world so far. To control the spread of the disease, screening large numbers of suspected cases for appropriate quarantine and treatment are a priority. Pathogenic laboratory testing is typically the gold standard, but it bears the burden of significant false negativity, adding to the urgent need of alternative diagnostic methods to combat the disease. Based on COVID-19 radiographic changes in CT images, this study hypothesized that artificial intelligence methods might be able to extract specific graphical features of COVID-19 and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control.

Authors

  • Shuai Wang
    Department of Intensive Care Unit, China-Japan Union Hospital of Jilin University, Changchun, China.
  • Bo Kang
    College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China.
  • Jinlu Ma
    Department of Radiation Oncology, First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
  • Xianjun Zeng
    Department of Radiology, Nanchang University First Hospital, Nanchang, China.
  • Mingming Xiao
    Department of Biochemistry and Molecular Biology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China.
  • Jia Guo
    Department of Radiology, Stanford University, Stanford, CA, USA.
  • Mengjiao Cai
    Department of Radiation Oncology, First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
  • Jingyi Yang
    Department of Radiation Oncology, First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
  • Yaodong Li
    Department of Radiology, No.8 Hospital, Xi'an Medical College, Xi'an, China.
  • Xiangfei Meng
    National Supercomputer Center in Tianjin, Tianjin, 300457, China. mengxf@nscc-tj.cn.
  • Bo Xu
    State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.

Keywords

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