The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
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.
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Cites
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Self-citationFeature Pyramid Networks for Object Detection
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“Thus, SARSCoV-2 infection cannot be entirely excluded, even if RT-PCR results from a suspected patient are negative [10]–[12].”
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Cited by
Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images
Fan, D.-P., Zhou, T., Ji, G.-P., Zhou, Y., Chen, G., Fu, H., Shen, J., & Shao, L. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.2996645 · Cited by 1,259
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Applications of artificial intelligence in battling against covid-19: A literature review
Tayarani N., M.-H. (2021) · Chaos, Solitons & Fractals · doi:10.1016/j.chaos.2020.110338 · Cited by 210
Metadata
- Authors
- 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.
- Venue
- IEEE Reviews in Biomedical Engineering
- Published
- 2021
- Volume
- 14
- Pages
- 16-29
- ISSN
- 1937-3333 (ISSN-L)
- 1941-1189
- OpenAlex
- W3022592783
- Cited by
- 401
- References
- 12
- FWCI
- 38.66
- Type
- journal article
- Language
- en
- Open access
- closed
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