Predicting The Stages Of Covid-19 Affected Patients Using CNN With CT Scan

Abstract

Battling the progressing Covid sickness 2019 (COVID-19) pandemic requests precise, quick, and point-of-care testing with quick outcomes to anticipate stages for isolation and therapy. The preliminary test to detect COVID-19 is a Swab test and also a Blood test, but these tests will take more than 2 days to receive the results and there is also a risk of transmission of the virus while collecting the samples. To predict the stages of COVID-19's effects on the human lungs accurately for further treatment for further diagnosis on a radiological image, medical experts need a high level of precision. We utilize image processing techniques and convolutional networks to analyze CT images of COVID-19 affected human lungs in this paper for the detection of pulmonary abnormalities in the early stage, Chest X-Ray is not exact. So, we are using Computed Tomography (CT) imaging especially for identifying the stages of lung anomalies. We present and discuss the scoring systems which cause the severity in lungs of COVID-19 patients every day. This will be accurate for predicting the stages of COVID-19 for early treatment and also to protect the uninfected population.