Identifying COVID-19 Pneumonia using Chest Radiography using Deep Convolutional Neural Networks

The limitations in data availability unwrap the horizons to open undedicated research into the COVID-19 pandemic. To contain the spread of the disease, proper detection, appropriate seclusion, and treatment are the need of the hour. The main challenge is to develop an economical, fast tool for the effective detection of viruses. In this paper, the authors aim to extract those regions rapidly that may contain features of COVID-19 from chest X-ray images and further classify the possible existence of Covid disease. It is evident that the proposed approach can efficiently contribute to the detection of COVID-19 disease and the overall classification rate obtained is 91.08% with a minimum loss of 0.0846 for 3-class based classification.