Deep-learning based detection of COVID-19 using lung ultrasound imagery.

Journal: PloS one
Published Date:

Abstract

BACKGROUND: The COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide, especially in underdeveloped countries. There is a clear need to develop novel computer-assisted diagnosis tools to provide rapid and cost-effective screening in places where massive traditional testing is not feasible. Lung ultrasound is a portable, easy to disinfect, low cost and non-invasive tool that can be used to identify lung diseases. Computer-assisted analysis of lung ultrasound imagery is a relatively recent approach that has shown great potential for diagnosing pulmonary conditions, being a viable alternative for screening and diagnosing COVID-19.

Authors

  • Julia Diaz-Escobar
    CICESE Research Center, Ensenada, Baja California, México.
  • Nelson E Ordóñez-Guillén
    CICESE Research Center, Ensenada, Baja California, México.
  • Salvador Villarreal-Reyes
    CICESE Research Center, Ensenada, Baja California, México.
  • Alejandro Galaviz-Mosqueda
    CICESE Research Center, Ensenada, Baja California, México.
  • Vitaly Kober
    CICESE Research Center, Ensenada, Baja California, México.
  • Raúl Rivera-Rodriguez
    CICESE Research Center, Ensenada, Baja California, México.
  • Jose E Lozano Rizk
    CICESE Research Center, Ensenada, Baja California, México.