Covid-19 Detection Using CNN Model with CT Scan Images

Abstract

Corona virus, a serious respiratory viral disease, has been spreading fast all over the world since the beginning of 2020. Over 30 million individuals and even more than normal rate have contracted the illness, and millions have died as a result. Despite the fact that there are various vaccines available right now, positive cases are still on the rise. The virus can spread in tiny liquid particles from the lips or nose of an infected person when they speak, sing, sneeze, cough, or breathe. These particles are various, ranging from larger respiratory droplets to small aerosols. We will create a CNN (Convolutional Neural Networks) model to predict if a person has covid or not using CT (Computed Tomography) scan images because the diagnostic kits and related resources are insufficient due to the increase in covid cases. A CT scan is a helpful diagnostic tool for identifying illnesses and injuries. It creates a 3D image of the soft tissues and bones using a succession of X-rays and a computer. In a hospital or imaging facility, you might receive a CT scan. Using the developed models, covid-19 was identified. As a fast and significant method to identify covid-19, doctors can use CT scan images in conjunction with automated identification as corona virus.