Detection of COVID-19 using CNN from Chest X-ray Images

ABSTRACT

COVID-19 (novel coronavirus disease) is a deadly illness, has infected and killed a very large number of people worldwide. The widely followed lab testing (RT-PCR Test) for the detection of this disease has various limitations with high cost and take long time to provide the outcome. As a result, diverse technologies that permit for the quick and accurate finding of the infection can provide much required assistance to medical management. In recent studies, gained radiological imaging techniques, such images convey important information about this virus. Advanced Deep learning (DL) techniques combined with the radiology images can aid in the correct diagnosis of the virus, as well as defeat the problem of insufficient expert physicians in rural areas. In this work, aimed at presenting a DL based-Convolutional neural network (CNN) model for the automatic detection of the coronavirus from X-ray images of chest. The Kaggle dataset available publicly of total 42330 images from 4-categories are used. The experiment produced the accuracy of 88.53% and 86.19% for training and validation, which is better result for the highest number of radiographic images in comparison to existing work. © 2022 IEEE.