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

被引:18
|
作者
Shaikh, Faiq [1 ]
Andersen, Michael Brun [2 ,7 ]
Sohail, M. Rizwan [3 ]
Mulero, Francisca [4 ]
Awan, Omer [5 ]
Dupont-Roettger, Diana [1 ]
Kubassova, Olga [1 ]
Dehmeshki, Jamshid [1 ,8 ]
Bisdas, Sotirios [6 ]
机构
[1] Image Anal Grp, Philadelphia, PA 19104 USA
[2] Aarhus Univ, Aarhus, Denmark
[3] Mayo Clin, Coll Med & Sci, Rochester, MN USA
[4] Ctr Nacl Invest Oncol, Madrid, Spain
[5] Univ Maryland, Baltimore, MD 21201 USA
[6] UCL, London, England
[7] Herlev Gentofte Hosp, Herlev, Denmark
[8] Kingston Univ, Kingston Upon Thames, Surrey, England
关键词
FDG-PET; INFECTION;
D O I
10.1067/j.cpradiol.2020.06.009
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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. (C) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页码:430 / 435
页数:6
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