Medical Imaging and its Role in Detection of COVID-19

Abstract

We critically analysed and systematically comprehended the Images of X-ray and CT Scans for COVID-19 Lungs. We tried to figure out the practical application of that procedure with the prevailing ecosystem while also considering the user friendliness. The whole major piece has been split into 3 umbrella terms namely, X-Ray, CT Scan and COVID-19. The present paper creates a base for these terminologies. Henceforth we can say that this paper creates such an atmosphere that elevates a prudent man's understanding to understand the complex and high indulgent of science and technology.It is true to say that the paper serves the purpose of being called analogical paper to such a height that the further research of the paper addresses the identification/detection of the COVID-19 reports and also differentiating them with reports having symptoms that are synonymous to task in hand. The conclusion of this paper ideally focuses on delineating the result coherently.

Architecture of Deep Learning and Its Applications

“…Deep learning is used to evaluate the impacted region of the body like cancer, bone issues, accidents, besides to lung ailments using X-ray diagnostics [11,13]. Mishra [70] et al, employed CNN-based models ResNet-50, and Inception-ResNet-v2 to predict COVID-19 patients via chest X-ray images and ResNet-50 had the optimal detection percentage (98%), according to them. The feature extraction procedure with chest X-ray pictures also uses DL algorithm and a support vector machine (SVM) to identify the image as healthy or diseased.…”