Automatic Covid-19 Chest CT Image Classification

Abstract

Background and Purpose: COVID-19 pandemic as a Public Health Emergency of International Concern in January 2020, we can know that the severity in that moment. COVID-19 pandemic influences many areas from world economics to personal health. Base on COVID-19 pandemic can be distinguish by CT chest image, our project is we wish to building a high-performance COVID-19 chest image classifier. Material and Method: Our classifier make up by CT chest image in 416 COVID-19 patients, 412 common pneumonia patients, and 270 health patients. We use the neural network as the classifier of CT image. In order to make the result more dependable and visualization, we are going to build the website user interface, the diagnostic result of the chest CT image and network model will show on website. The website structure as following. 1. Introduction of the project (including Motivation, Technical Challenges, and Project Objectives) 2. Related work 3. Basic ideas of the platform(s), solution(s), and contribution(s) Results: Our model can accurately identify three kinds of patients, common pneumonia patients, COVID-19 patients, and health patients. Following accuracy is 86.67%, 94.59%, and 97.37%