Classification of Coronavirus Disease (COVID-19) using Convolutional Neural Networks (CNN) Architecture

Abstract

An infectious illness caused by a recently identified virus is known as Coronavirus Disease (COVID-19). COVID-19 infection is usually associated with mild to moderate respiratory disease, and no specific treatment is usually required. A higher risk of severe sickness exists among the elderly and in individuals who have primary medical issues such as chronic respiratory disease, diabetes, cancer, and cardiovascular diseases. If the information needed for a diagnosis or prognosis can only be retrieved via 3D volumetric imaging under these conditions, this becomes a significant asset for coronavirus affected patients. In this research, we present a novel technique for detecting the 3D volumetric respiratory image and categorising COVID-19 infection. We have utilised 3D image processing and the methods of deep learning for the procedure of classification and detection.