Using Deep Learning Algorithms in Chest X-ray Image COVID-19 Diagnosis

Yu Chih Chang, An Shun Liu, Woei Chyn Chu*

*此作品的通信作者

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

We are experiencing heavy COVID-19 outbroke globally since January 2020. In Taiwan, because its low infection rate (< 0.01%), there was not enough evidence for diagnosis through medical imaging. At present, chest X-ray is widely used in lung infection diagnoses. This study uses deep learning methods to assist doctors in classifying COVID-19 disease from chest X-ray images. After pre-processing, the images were put into the VGG16 model to automaticallyclassify into three categories to assist the radiologist in the treatment of the disease. The results show that the classification accuracy was 78%. Detail analyses disclosed that this accuracy can be improved by rectifying the unbalanced images problem. In addition, choosing proper image pre-processing algorithms has a high tendency to generate better results.

原文English
主出版物標題3rd IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2021
編輯Teen-Hang Meen
發行者Institute of Electrical and Electronics Engineers Inc.
頁面74-76
頁數3
ISBN(電子)9781728193045
DOIs
出版狀態Published - 2021
事件3rd IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2021 - Tainan, 台灣
持續時間: 28 5月 202130 5月 2021

出版系列

名字3rd IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2021

Conference

Conference3rd IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2021
國家/地區台灣
城市Tainan
期間28/05/2130/05/21

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