The Role of Imaging in the Detection and Management of COVID-19: A Review

Di Dong; Zhenchao Tang; Shuo Wang; Hui Hui; Lixin Gong; Yao Lu; Zhong Xue; Hongen Liao; Fang Chen; Fan Yang; Ronghua Jin; Kun Wang; Zhenyu Liu; Jingwei Wei; Wei Mu; Hui Zhang; Jingying Jiang; Jie Tian; Hongjun Li

doi:10.1109/RBME.2020.2990959

The Role of Imaging in the Detection and Management of COVID-19: A Review

Di Dong
, Zhenchao Tang
, Shuo Wang
, Hui Hui
, Lixin Gong
, Yao Lu
, Zhong Xue
, Hongen Liao
, Fang Chen
, Fan Yang
, Ronghua Jin
, Kun Wang
, Zhenyu Liu
, Jingwei Wei
, Wei Mu
, Hui Zhang
, Jingying Jiang
, Jie Tian^*
, Hongjun Li^*

^*Corresponding author for this work

Chinese Academy of Sciences
Beihang University
Northeastern University China
Sun Yat-Sen University
Central Research Institute
Tsinghua University
Nanjing University of Aeronautics and Astronautics
Huazhong University of Science and Technology
Capital Medical University
CAS - Institute of Automation

Research output: Contribution to journal › Article › peer-review

312 Scopus citations

Abstract

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in diagnosis and treatment assessment of the disease. Herein, we review the imaging characteristics and computing models that have been applied for the management of COVID-19. CT, positron emission tomography - CT (PET/CT), lung ultrasound, and magnetic resonance imaging (MRI) have been used for detection, treatment, and follow-up. The quantitative analysis of imaging data using artificial intelligence (AI) is also explored. Our findings indicate that typical imaging characteristics and their changes can play crucial roles in the detection and management of COVID-19. In addition, AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of COVID-19.

Original language	English
Article number	9079648
Pages (from-to)	16-29
Number of pages	14
Journal	IEEE Reviews in Biomedical Engineering
Volume	14
DOIs	https://doi.org/10.1109/RBME.2020.2990959
State	Published - 2021
Externally published	Yes

Keywords

COVID-19
artificial intelligence
chest CT
imaging

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Dong, D., Tang, Z., Wang, S., Hui, H., Gong, L., Lu, Y., Xue, Z., Liao, H., Chen, F., Yang, F., Jin, R., Wang, K., Liu, Z., Wei, J., Mu, W., Zhang, H., Jiang, J., Tian, J., & Li, H. (2021). The Role of Imaging in the Detection and Management of COVID-19: A Review. IEEE Reviews in Biomedical Engineering, 14, 16-29. Article 9079648. https://doi.org/10.1109/RBME.2020.2990959

@article{52cc453ee3314fa291004a83509a1abf,

title = "The Role of Imaging in the Detection and Management of COVID-19: A Review",

abstract = "Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in diagnosis and treatment assessment of the disease. Herein, we review the imaging characteristics and computing models that have been applied for the management of COVID-19. CT, positron emission tomography - CT (PET/CT), lung ultrasound, and magnetic resonance imaging (MRI) have been used for detection, treatment, and follow-up. The quantitative analysis of imaging data using artificial intelligence (AI) is also explored. Our findings indicate that typical imaging characteristics and their changes can play crucial roles in the detection and management of COVID-19. In addition, AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of COVID-19.",

keywords = "COVID-19, artificial intelligence, chest CT, imaging",

author = "Di Dong and Zhenchao Tang and Shuo Wang and Hui Hui and Lixin Gong and Yao Lu and Zhong Xue and Hongen Liao and Fang Chen and Fan Yang and Ronghua Jin and Kun Wang and Zhenyu Liu and Jingwei Wei and Wei Mu and Hui Zhang and Jingying Jiang and Jie Tian and Hongjun Li",

note = "Publisher Copyright: {\textcopyright} 2008-2011 IEEE.",

year = "2021",

doi = "10.1109/RBME.2020.2990959",

language = "英语",

volume = "14",

pages = "16--29",

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TY - JOUR

T1 - The Role of Imaging in the Detection and Management of COVID-19

T2 - A Review

AU - Dong, Di

AU - Tang, Zhenchao

AU - Wang, Shuo

AU - Hui, Hui

AU - Gong, Lixin

AU - Lu, Yao

AU - Xue, Zhong

AU - Liao, Hongen

AU - Chen, Fang

AU - Yang, Fan

AU - Jin, Ronghua

AU - Wang, Kun

AU - Liu, Zhenyu

AU - Wei, Jingwei

AU - Mu, Wei

AU - Zhang, Hui

AU - Jiang, Jingying

AU - Tian, Jie

AU - Li, Hongjun

PY - 2021

Y1 - 2021

N2 - Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in diagnosis and treatment assessment of the disease. Herein, we review the imaging characteristics and computing models that have been applied for the management of COVID-19. CT, positron emission tomography - CT (PET/CT), lung ultrasound, and magnetic resonance imaging (MRI) have been used for detection, treatment, and follow-up. The quantitative analysis of imaging data using artificial intelligence (AI) is also explored. Our findings indicate that typical imaging characteristics and their changes can play crucial roles in the detection and management of COVID-19. In addition, AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of COVID-19.

AB - Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in diagnosis and treatment assessment of the disease. Herein, we review the imaging characteristics and computing models that have been applied for the management of COVID-19. CT, positron emission tomography - CT (PET/CT), lung ultrasound, and magnetic resonance imaging (MRI) have been used for detection, treatment, and follow-up. The quantitative analysis of imaging data using artificial intelligence (AI) is also explored. Our findings indicate that typical imaging characteristics and their changes can play crucial roles in the detection and management of COVID-19. In addition, AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of COVID-19.

KW - COVID-19

KW - artificial intelligence

KW - chest CT

KW - imaging

UR - https://www.scopus.com/pages/publications/85084208192

U2 - 10.1109/RBME.2020.2990959

DO - 10.1109/RBME.2020.2990959

M3 - 文章

C2 - 32356760

AN - SCOPUS:85084208192

SN - 1937-3333

VL - 14

SP - 16

EP - 29

JO - IEEE Reviews in Biomedical Engineering

JF - IEEE Reviews in Biomedical Engineering

M1 - 9079648

ER -

The Role of Imaging in the Detection and Management of COVID-19: A Review

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