Deep Learning on Chest X-Ray Images for Lung Abnormality Detection to Identify COVID-19 And Pneumonia

Authors

  • Reetu Jain

Abstract

The novel coronavirus (COVID-19) has infected over 131 million people worldwide and killed nearly 3 million. It is extremely disheartening to witness the world suffering from this pandemic which has taken the lives of so many.. At the moment, according to WHO COVID-19 is considered one of the most dangerous diseases caused by this novel coronavirus which was found to have originated in Wuhan (China) towards the end of 2019. An early diagnosis of COVID-19 through effective means, such as X-ray images, can greatly help in reducing the fatality rate of this disease by preventing it from developing into Pneumonia. In this research, we suggest an efficient means to detect COVID-19 and Pneumonia with the help of a deep learning algorithm which can give results up to an 87% accuracy. One of the most important aspects of this research paper is that we’ve built our own deep learning algorithm to distinguish between Pneumonia, COVID-19,  and normal lungs using an X-ray image dataset to teach the algorithm.

Downloads

Published

2022-06-18

How to Cite

Jain, R. (2022). Deep Learning on Chest X-Ray Images for Lung Abnormality Detection to Identify COVID-19 And Pneumonia. iJournals:International Journal of Software & Hardware Research in Engineering ISSN:2347-4890, 10(6). Retrieved from https://ijournals.in/journal/index.php/ijshre/article/view/137

Most read articles by the same author(s)

1 2 > >>