A Survey on Artificial Intelligence in Chest Imaging of COVID-19
Abstract
The coronavirus disease 2019 (COVID-19) has infected more than 9.3 million people and has caused over 0.47 million deaths worldwide as of June 24, 2020. Chest imaging techniques including computed tomography and X-ray scans are indispensable tools in COVID-19 diagnosis and its management. The strong infectiousness of this disease brings a huge burden for radiologists. In order to overcome the difficulty and improve accuracy of the diagnosis, artificial intelligence (AI)-based imaging analysis methods are explored. This survey focuses on the development of chest imaging analysis methods based on AI for COVID-19 in the past few months. Specially, we first recall imaging analysis methods of two typical viral pneumonias, which can provide a reference for studying the disease on chest images. We further describe the development of AI-assisted diagnosis and assessment for the disease, and find that AI techniques have great advantage in this application.
The coronavirus disease 2019 (COVID-19) has infected more than 9.3 million people and has caused over 0.47 million deaths worldwide as of June 24, 2020. Chest imaging techniques including computed tomography and X-ray scans are indispensable tools in COVID-19 diagnosis and its management. The strong infectiousness of this disease brings a huge burden for radiologists. In order to overcome the difficulty and improve accuracy of the diagnosis, artificial intelligence (AI)-based imaging analysis methods are explored. This survey focuses on the development of chest imaging analysis methods based on AI for COVID-19 in the past few months. Specially, we first recall imaging analysis methods of two typical viral pneumonias, which can provide a reference for studying the disease on chest images. We further describe the development of AI-assisted diagnosis and assessment for the disease, and find that AI techniques have great advantage in this application.
Keywords: Artificial intelligence; COVID-19; chest imaging analysis; deep learning; imaging findings
Document Type: Research Article
Affiliations: 1: School of Mathematics and Computational Science, Xiangtan University, Xiangtan, China 2: School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China 3: School of Mathematics, Sun Yat-sen University, Guangzhou, China
Publication date: 16 December 2020
This article was made available online on 10 November 2020 as a Fast Track article with title: "A Survey on Artificial Intelligence in Chest Imaging of COVID-19".
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