Classification of Chest X-ray Images to Diagnose Covid-19 using Deep Learning Techniques

Isabel Silva, Ramoni Negreiros, André Alves, André Alves, Dalton Valadares, Dalton Valadares, Dalton Valadares, Angelo Perkusich, Angelo Perkusich

2022

Abstract

The new coronavirus pandemic has brought disruption to the world. One of the significant dilemmas to be solved by countries, especially in underdeveloped countries like Brazil, is the lack of mass testing for the population. An alternative to these tests is detecting the disease through the analysis of radiographic images. To process different types of images automatically, we employed deep learning algorithms to achieve success in recognizing different diagnostics. This work aims to train a deep learning model capable of automatically recognizing the Covid-19 diagnosis through radiographic images. Comparing images of coronavirus, healthy lung, and bacterial and viral pneumonia, we obtained a result with 94% accuracy.

Paper Citation

in Harvard Style

Silva I., Negreiros R., Alves A., Valadares D. and Perkusich A. (2022). Classification of Chest X-ray Images to Diagnose Covid-19 using Deep Learning Techniques. In Proceedings of the 19th International Conference on Wireless Networks and Mobile Systems - Volume 1: WINSYS, ISBN 978-989-758-592-0, pages 93-100. DOI: 10.5220/0011339700003286

in Bibtex Style

@conference{winsys22,
author={Isabel Silva and Ramoni Negreiros and André Alves and Dalton Valadares and Angelo Perkusich},
title={Classification of Chest X-ray Images to Diagnose Covid-19 using Deep Learning Techniques},
booktitle={Proceedings of the 19th International Conference on Wireless Networks and Mobile Systems - Volume 1: WINSYS,},
year={2022},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011339700003286},
isbn={978-989-758-592-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Wireless Networks and Mobile Systems - Volume 1: WINSYS,
TI - Classification of Chest X-ray Images to Diagnose Covid-19 using Deep Learning Techniques
SN - 978-989-758-592-0
AU - Silva I.
AU - Negreiros R.
AU - Alves A.
AU - Valadares D.
AU - Perkusich A.
PY - 2022
SP - 93
EP - 100
DO - 10.5220/0011339700003286