Real-Time Diagnosis System of COVID-19 Using X-Ray Images and Deep Learning.

Real-Time Diagnosis System of COVID-19 Using X-Ray Images and Deep Learning.
Author(s):
Suveer Kumar, Abhinandan Kr., Syed Wahid Ali, Vineet Ranjan, Dipti Patnayak, Dr. Aruna M G, Dr. Malatesh S H
Keywords:

Abstract
The novel coronavirus named COVID-19 has quickly spread among humans worldwide, and the situation remains hazardous to the health system. The existence of this virus in the human body is identified through sputum or blood samples. Furthermore, computed tomography (CT) or X-ray has become a significant tool for quick diagnoses. Thus, it is essential to develop an online and real-time computer aided diagnosis (CAD) approach to support physicians and avoid further spreading of the disease. In this research, a convolutional neural network (CNN) -based Residual neural network (ResNet50) has been employed to detect COVID-19 through chest X-ray images and achieved 98% accuracy. The proposed CAD system will receive the X-ray images from the remote hospitals/healthcare centres and perform diagnostic processes. Furthermore, the proposed CAD system uses advanced load balancer and resilience features to achieve fault tolerance with zero delays and perceives more infected cases during this pandemic.
Article Details
Unique Paper ID: 156220 Publication Volume & Issue: Volume 9, Issue 3 Page(s): 36 - 40
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org