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A Survey of COVID-19 Detection From Chest X-Rays Using Deep Learning Methods

Author

Listed:
  • Bhargavinath Dornadula

    (Vellore Institute of Technology, Chennai, India)

  • S. Geetha

    (Vellore Institute of Technology, Chennai, India)

  • L. Jani Anbarasi

    (Vellore Institute of Technology, Chennai, India)

  • Seifedine Kadry

    (Department of Applied Data Science, Noroff University College, Kristiansand, Norway & Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, UAE & Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon)

Abstract

The coronavirus (COVID-19) outbreak has opened an alarming situation for the whole world and has been marked as one of the most severe and acute medical conditions in the last hundred years. Various medical imaging modalities including computer tomography (CT) and chest x-rays are employed for diagnosis. This paper presents an overview of the recently developed COVID-19 detection systems from chest x-ray images using deep learning approaches. This review explores and analyses the data sets, feature engineering techniques, image pre-processing methods, and experimental results of various works carried out in the literature. It also highlights the transfer learning techniques and different performance metrics used by researchers in this field. This information is helpful to point out the future research direction in the domain of automatic diagnosis of COVID-19 using deep learning techniques.

Suggested Citation

  • Bhargavinath Dornadula & S. Geetha & L. Jani Anbarasi & Seifedine Kadry, 2022. "A Survey of COVID-19 Detection From Chest X-Rays Using Deep Learning Methods," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 18(1), pages 1-16, January.
    • Handle: RePEc:igg:jdwm00:v:18:y:2022:i:1:p:1-16
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