COVID-19 Detection in Chest X-ray Images using a Deep Learning Approach

Author
Keywords
Abstract
The Corona Virus Disease (COVID-19) is an infectious disease caused by a new virus that has not been detected in humans before. The virus causes a respiratory illness like the flu with various symptoms such as cough or fever that, in severe cases, may cause pneumonia. The COVID-19 spreads so quickly between people, affecting to 1,200,000 people worldwide at the time of writing this paper (April 2020). Due to the number of contagious and deaths are continually growing day by day, the aim of this study is to develop a quick method to detect COVID-19 in chest X-ray images using deep learning techniques. For this purpose, an object detection architecture is proposed, trained and tested with a public available dataset composed with 1500 images of non-infected patients and infected with COVID-19 and pneumonia. The main goal of our method is to classify the patient status either negative or positive COVID-19 case. In our experiments using SDD300 model we achieve a 94.92% of sensibility and 92.00% of specificity in COVID-19 detection, demonstrating the usefulness application of deep learning models to classify COVID-19 in X-ray images.
Year of Publication
2020
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
6
Start Page
11
Issue
Regular Issue
Number
2
Number of Pages
4
Date Published
06/2020
ISSN Number
1989-1660
Citation Key
URL
https://www.ijimai.org/journal/sites/default/files/2020-05/ijimai_6_2_2.pdf
DOI
10.9781/ijimai.2020.04.003
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