COVID-19 detection using chest X-ray images based on a developed deep neural network.

Journal: SLAS technology
Published Date: Oct 25, 2021

Abstract

AIM: Currently, a new coronavirus called COVID-19 is the biggest challenge of the human at 21st century. Now, the spread of this virus is such that mortality has risen strongly in all cities of countries. Therefore, it is necessary to think of a solution to handle the disease by fast and timely diagnosis. This paper proposes a method that uses chest X-ray imagery to divide 2-4 classes into 7 different Scenarios, including Bacterial, Viral, Healthy, and COVID-19 classes. The aim of this study is to propose a method that uses chest X-ray imagery to divide 2-4 classes into 7 different Scenarios, including Bacterial, Viral, Healthy, and COVID-19 classes.

Authors

  • Zohreh Mousavi
    Department of Mechanical Engineering, Faculty of Mechanical Engineering, University of Tabriz, Tabriz, Iran. Electronic address: zohreh.mousavi@tabrizu.ac.ir.
  • Nahal Shahini
    Deparment of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran. Electronic address: shahini.nahal@aut.ac.ir.
  • Sobhan Sheykhivand
    Department of Biomedical Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran. Electronic address: s.sheykhivand@tabrizu.ac.ir.
  • Sina Mojtahedi
    Department of Electrical and Electronics Engineering, Faculty of Engineering, Okan University, Istanbul, Turkey.
  • Afrooz Arshadi
    Department of statiatics, Faculty of Mathematical sciences and computer, University of Allameh Tabataba'i, Tehran, Iran.

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