Detection Covid-19 Based on Chest X-ray Images Using ConVolution Neural Networks

Authors

• Sufyan Othman Zaben, Department of Computer Science, University of Technology, Baghdad, IraqFollow
• Akbas Ezaldeen, Department of Computer Science, University of Technology, Baghdad, IraqFollow

Document Type

Original Study

Keywords

Computer Engineering

Abstract

Covid-19 is a deadly virus that has spread worldwide, causing millions of deaths. Chest X-ray is one of the most common methods of diagnosing the infection of Covid - 19. Therefore, this paper has presented an efficient method to detect Covid-19 through X-rays of the chest area through a Neural conVolution network (CNN). the proposed system has used a conVolution neural network to classify the extracted features. Since CNN needs a set of data defined for training and testing, the proposed method used a public dataset of 350 pneumonia x-ray images, 300 viral images, and 350 normal images for evaluation. Besides, the proposed work achieved a satisfactory accuracy of 95% based on the X-ray image.

How to Cite This Article

Zaben, Sufyan Othman and Ezaldeen, Akbas (2022) "Detection Covid-19 Based on Chest X-ray Images Using ConVolution Neural Networks," Iraqi Journal of Computers, Communications, Control and Systems Engineering: Vol. 22: Iss. 1, Article 4.
DOI: 10.33103/uot.ijccce.22.1.4
Available at: https://ijccce.researchcommons.org/journal/vol22/iss1/4