A survey of AI imaging techniques for COVID-19 diagnosis and prognosis

• Autorzy: Tellakula K K Praneeth , Kumar Saravana , Deb Sanjoy

Identyfikatory

DOI

10.23743/acs-2021-12

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

artificial intelligence; COVID-19; diagnosis; follow-up; prognosis

PL

sztuczna inteligencja; COVID-19; diagnoza; obserwacja; prognoza

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2021
• Tom: Vol. 17, no 2
• Strony: 40--55
• Opis fizyczny: Bibliogr. 48 poz., fig., tab.

Twórcy

autor

Tellakula K K Praneeth

• Bannari Amman Institute of Technology (Anna University, Department of Electronics And Communication Engineering), Sathyamangalam, India

• https://orcid.org/0000-0002-3346-7251

autor

Kumar Saravana

• Bannari Amman Institute of Technology (Anna University, Department of Electronics And Communication Engineering), Sathyamangalam, India

• https://orcid.org/0000-0002-8307-6208

autor

Deb Sanjoy

• Bannari Amman Institute of Technology (Anna University, Department of Electronics And Communication Engineering), Sathyamangalam, India

• https://orcid.org/0000-0002-0186-3938

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).