ACS Applied Computer Science

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A SURVEY OF AI IMAGING TECHNIQUES FOR COVID-19 DIAGNOSIS AND PROGNOSIS

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The Coronavirus Disease 2019 (COVID-19) has caused massive infections and death toll. Radiological imaging in chest such as computed tomography (CT) has been instrumental in the diagnosis and evaluation of the lung infection which is the common indication in COVID-19 infected patients. The technological advances in artificial intelligence (AI) furthermore increase the performance of imaging tools and support health professionals. CT, Positron Emission Tomography – CT (PET/CT), X-ray, Magnetic Resonance Imaging (MRI), and Lung Ultrasound (LUS) are used for diagnosis, treatment of COVID-19. Applying AI on image acquisition will help automate the process of scanning and providing protection to lab technicians. AI empowered models help radiologists and health experts in making better clinical decisions. We review AI-empowered medical imaging characteristics, image acquisition, computer-aided models that help in the COVID-19 diagnosis, management, and follow-up. Much emphasis is on CT and X-ray with integrated AI, as they are first choice in many hospitals.

  • APA 7th style
Tellakula, K. K. P., Kumar, S., & Deb, S. (2021). A survey of ai imaging techniques for COVID-19 diagnosis and prognosis. Applied Computer Science, 17(2), 40-55. https://doi.org/10.23743/acs-2021-12
  • Chicago style
Tellakula, K K Praneeth, Saravana Kumar, and Sanjoy Deb. "A Survey of Ai Imaging Techniques for Covid-19 Diagnosis and Prognosis." Applied Computer Science 17, no. 2 (2021): 40-55.
  • IEEE style
K. K. P. Tellakula, S. Kumar, and S. Deb, "A survey of ai imaging techniques for COVID-19 diagnosis and prognosis," Applied Computer Science, vol. 17, no. 2, pp. 40-55, 2021, doi: 10.23743/acs-2021-12.
  • Vancouver style
Tellakula KKP, Kumar S, Deb S. A survey of ai imaging techniques for COVID-19 diagnosis and prognosis. Applied Computer Science. 2021;17(2):40-55.