Convolutional neural network for prediction of COVID-19 from chest X-ray images

Abstract

The COVID-19 pandemic has affected humans worldwide, and we are in dire need of techniques to bring this situation within our control. Among the various approaches attempted by researchers, preliminary prediction of COVID-19 through chest X-ray images is proving to be quite beneficial and thus, is being explored thoroughly. In this paper, a novel combination of local binary pattern based feature selection along with a convolutional neural network is proposed which can predict positive and negative cases by analysing chest X-ray images. The model consists of a feature extraction process followed by various pooling and convolution layers systematically placed to give an optimal output. The proposed model has been trained and tested on a COVID-19 CXR images dataset, and it is seen that it achieves a significant improvement over the five other comparison methods.