A deep neural network for detecting coronavirus disease using chest X-ray images

Abstract

COVID-19 is one of the leading causes of death worldwide in the year 2020 and was declared a pandemic by the World Health Organization (WHO). This virus affects all countries across the world and 5 lakh people died as of June 2020 due to COVID-19. Due to the highly contagious nature, early detection of this virus plays a vital role to break the covid chain. Recent studies done by China say that chest CT and x-ray image may be used as a preliminary test for covid detection. Deep learning-based CNN model can detect coronavirus automatically from the chest x-ray images. This paper proposed a transfer learning-based approach to detect covid disease. Due to the low number of covid chest images, the authors are using a pre-trained model to classify x-ray images into covid and normal classes. This paper presents the comparative study of various pre-trained models like VGGNet-19, ResNet50, and Inception_ResNet_V2. Experiment results show that Inception_ResNet_V2 gives better results than VGGNet and ResNet models with training and test accuracy of 99.26 and 94, respectively.