A Review of Automatically Diagnosing COVID-19 based on Scanning Image

The pandemic of COVID-19 has caused millions of infectious. Due to the false-negative rate and the time cost of conventional RT-PCR tests, X-ray images and Computed Tomography (CT) images based diagnosing become widely adopted. Therefore, researchers of the computer vision area have developed many automatic diagnosing models to help the radiologists and pro-mote the diagnosing accuracy. In this paper, we present a review of these recently emerging automatic diagnosing models. 62 models from 14, February to 5, May, 2020 are involved. We analyzed the models from the perspective of preprocessing, feature extraction, classification, and evaluation. Then we pointed out that domain adaption in transfer learning and interpretability promotion are the possible future directions.