Detection and Classification of COVID 19 using Convolutional Neural Network from Chest X-ray Images
Tatiana Chakravorti, Vinay Kumar Addala, Jyoti Verma
Abstract
In 2019 the novel Corona virus which is called COVID 19 was originated in China and now it has spread all over the world. So far more than 73M people got affected all over the world, most of the countries are searching for easy way to analyze. The increasing number of daily COVID 19 cases needs another solution and needs a lot of study. In this paper a deep learning model has been proposed for detection and classification of COVID 19 with high accuracy from chest x-ray. The tensor flow based CNN method has been proposed to classify using chest x-ray images. The proposed model has been trained and tested on the prepared dataset and it has been found that the overall accuracy achieved for the 2-class classification (COVID 19 vs Healthy) is 95%, and the precision and recall rate are 95%. The performance of the proposed model is very promising and it can be very helpful tool for radiologists and clinical practitioners in case of COVID 19 detection and classification because of its simplicity. More over this paper represent a comparative study of the proposed technique with ELM which will help researchers for further analysis.