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COVID-19 Imaging-based AI Research — A Literature Review

Author(s):

Cheng Ge, Lili Zhang, Liangxu Xie, Ren Kong, Hong Zhang and Shan Chang*  

Abstract:


Background: The new coronavirus disease 2019 (COVID-19) is spreading rapidly around the world. Artificial intelligence (AI) assisted identification and detection of diseases is an ef-fective method of medical diagnosis.

Objectives: To present recent advances in AI-assisted diagnosis of COVID-19, we introduce major aspects of AI in the process of diagnosing COVID-19.

Methods: In this paper, we firstly cover the latest collection and processing methods of da-tasets of COVID-19. The processing methods mainly include building public datasets, transfer learning, unsupervised learning and weakly supervised learning, semi-supervised learning methods and so on. Secondly, we introduce the algorithm application and evaluation metrics of AI in medical imaging segmentation and automatic screening. Then, we introduce the quantifi-cation and severity assessment of infection in COVID-19 patients based on image segmenta-tion and automatic screening. Finally, we analyze and point out the current AI-assisted diagno-sis of COVID-19 problems, which may provide useful clues for future work.

Conclusion: AI is critical for COVID-19 diagnosis. Combining chest imaging with AI can not only save time and effort, but also provide more accurate and efficient medical diagnosis results.

Keywords:

COVID-19, Artificial intelligence, Medical diagnosis, Medical imaging, Segmentation, AI-assisted

Affiliation:

Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, School of Mathematics, China University of Mining and Technology, Xuzhou, Jiangsu 221116, Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001



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