Current Landscape of Imaging and the Potential Role for Artificial Intelligence in the Management of COVID-19.

Journal: Current problems in diagnostic radiology
Published Date: Jun 27, 2020

Abstract

The clinical management of COVID-19 is challenging. Medical imaging plays a critical role in the early detection, clinical monitoring and outcomes assessment of this disease. Chest x-ray radiography and computed tomography) are the standard imaging modalities used for the structural assessment of the disease status, while functional imaging (namely, positron emission tomography) has had limited application. Artificial intelligence can enhance the predictive power and utilization of these imaging approaches and new approaches focusing on detection, stratification and prognostication are showing encouraging results. We review the current landscape of these imaging modalities and artificial intelligence approaches as applied in COVID-19 management.

Authors

  • Faiq Shaikh
    Institute of Computational Health Sciences, UCSF, San Francisco, California. Electronic address: faiq.shaikh@hotmail.com.
  • Michael Brun Andersen
    Aarhus University, Aarhus, Denmark; Herlev Gentofte Hospital, The Capital Region, Denmark.
  • M Rizwan Sohail
    Mayo Clinic College of Medicine and Science, Rochester, MN.
  • Francisca Mulero
    Molecular Imaging Unit, CNIO - Spanish National Cancer Research Center, Melchor Fernandez Almagro, 3, Madrid, 28029, Spain.
  • Omer Awan
    Department of Radiology, Temple University, Philadelphia, Pennsylvania.
  • Diana Dupont-Roettger
    Image Analysis Group, Philadelphia, PA, USA.
  • Olga Kubassova
    Image Analysis Group, London, United Kingdom.
  • Jamshid Dehmeshki
    Image Analysis Group, Philadelphia, PA, USA; Kingston University, Kingston-upon-Thames, UK.
  • Sotirios Bisdas
    Queen Square Institute of Neurology, University College London, Queen Square 7, London WC1N 3BG, UK.

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