CovMediScanX: A medical imaging solution for COVID-19 diagnosis from chest X-ray images.

Journal: Journal of medical imaging and radiation sciences
Published Date: Apr 8, 2024

Abstract

INTRODUCTION: Radiologists have extensively employed the interpretation of chest X-rays (CXR) to identify visual markers indicative of COVID-19 infection, offering an alternative approach for the screening of infected individuals. This research article presents CovMediScanX, a deep learning-based framework designed for a rapid and automated diagnosis of COVID-19 from CXR scan images.

Authors

  • Smitha Sunil Kumaran Nair
    Department of Computing and Electronics Engineering, Middle East College, Sultanate of Oman.
  • Leena R David
    Department of Medical Diagnostic Imaging, College of Health Sciences, University of Sharjah, United Arab Emirates. Electronic address: ldavid@sharjah.ac.ae.
  • Abdulwahid Shariff
    Department of Postgraduate Studies, University of Dar es Salaam, Tanzania.
  • Saqar Al Maskari
    Department of Computing and Electronics Engineering, Middle East College, Sultanate of Oman.
  • Adhra Al Mawali
    Quality Assurance and Planning, German University of Technology (GUtech), Sultanate of Oman.
  • Sammy Weis
    University Hospital, Sharjah, United Arab Emirates.
  • Taha Fouad
    University Hospital, Sharjah, United Arab Emirates.
  • Dilber Uzun Ozsahin
    Near East University, Nicosia/TRNC, Mersin-10, 99138, Turkey.
  • Aisha Alshuweihi
    University Hospital, Sharjah, United Arab Emirates.
  • Abdulmunhem Obaideen
    University Hospital, Sharjah, United Arab Emirates.
  • Wiam Elshami
    Medical Diagnostic Imaging Department, College of Health Sciences, University of Sharjah, Sharjah, UAE.

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