Skip to main content
Article | Green Intelligent Systems and Applications | Volume 1 - Issue 1 - 2021 | 12-18 | https://doi.org/10.53623/gisa.v1i1.32
© 2021 by the author(s), and is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License Creative Commons Attribution 4.0 International (CC BY 4.0) License

Chest X-Ray Classification of Lung Diseases Using Deep Learning

Author(s): Yew Fai Cheah
Author(s) information:
Faculty of Engineering and Science, Curtin University, Malaysia

Corresponding author

Green Intelligent Systems and Applications

Volume 1 - Issue 1 - 2021

 About the journal
Submit your article
Chest X-ray images can be used to detect lung diseases such as COVID-19, viral pneumonia, and tuberculosis (TB). These diseases have similar patterns and diagnoses, making it difficult for clinicians and radiologists to differentiate between them. This paper uses convolutional neural networks (CNNs) to diagnose lung disease using chest X-ray images obtained from online sources. The classification task is separated into three and four classes, with COVID-19, normal, TB, and viral pneumonia, while the three-class problem excludes the normal lung. During testing, AlexNet and ResNet-18 gave promising results, scoring more than 95% accuracy.
Read Full-Text
Previous article
Next article
Read Full-Text
About this article

SUBMITTED: 06 October 2021
ACCEPTED: 19 October 2021
PUBLISHED: 29 November 2021
SUBMITTED to ACCEPTED: 13 days
DOI: https://doi.org/10.53623/gisa.v1i1.32

Cite this article
Cheah, Y. F. (2021). Chest X-Ray Classification of Lung Diseases Using Deep Learning. Green Intelligent Systems and Applications, 1(1), 12–18. https://doi.org/10.53623/gisa.v1i1.32
Keywords
CNN COVID-19 tuberculosis viral pneumonia
Accessed
708
Citations
0
Share this article