• English
    • العربية
  • العربية
  • Login
  • QU
  • QU Library
  •  Home
  • Communities & Collections
View Item 
  •   Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Computer Science & Engineering
  • View Item
  • Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Computer Science & Engineering
  • View Item
  •      
  •  
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A review of deep learning-based detection methods for COVID-19

    Thumbnail
    View/Open
    Publisher version (You have accessOpen AccessIcon)
    Publisher version (Check access options)
    Check access options
    1-s2.0-S0010482522000257-main.pdf (4.267Mb)
    Date
    2022
    Author
    Subramanian, N.
    Elharrouss, O.
    Al-Maadeed, Somaya
    Chowdhury, M.
    Metadata
    Show full item record
    Abstract
    COVID-19 is a fast-spreading pandemic, and early detection is crucial for stopping the spread of infection. Lung images are used in the detection of coronavirus infection. Chest X-ray (CXR) and computed tomography (CT) images are available for the detection of COVID-19. Deep learning methods have been proven efficient and better performing in many computer vision and medical imaging applications. In the rise of the COVID pandemic, researchers are using deep learning methods to detect coronavirus infection in lung images. In this paper, the currently available deep learning methods that are used to detect coronavirus infection in lung images are surveyed. The available methodologies, public datasets, datasets that are used by each method and evaluation metrics are summarized in this paper to help future researchers. The evaluation metrics that are used by the methods are comprehensively compared.
    DOI/handle
    http://dx.doi.org/10.1016/j.compbiomed.2022.105233
    http://hdl.handle.net/10576/31076
    Collections
    • Computer Science & Engineering [‎2428‎ items ]
    • COVID-19 Research [‎848‎ items ]

    entitlement


    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Home

    Submit your QU affiliated work

    Browse

    All of Digital Hub
      Communities & Collections Publication Date Author Title Subject Type Language Publisher
    This Collection
      Publication Date Author Title Subject Type Language Publisher

    My Account

    Login

    Statistics

    View Usage Statistics

    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Video