Automated Detection and Classification of COVID-19 from Chest X-ray Images Using Deep Learning

Abstract

In recent times, COVID-19 has appeared as a major threat to healthcare professionals, governments, and research communities over the world from its diagnosis to medication. Several research works have been carried out for obtaining the possible solutions for controlling the epidemic proficiently. An effective diagnosis of COVID-19 has been carried out using computed tomography (CT) scans and X-rays to examine the lung image. But it necessitates diverse radiologists and time to examine every report, which is a tedious task. Therefore, this paper presents an automated deep learning (DL) based COVID-19 detection and classification model. The presented model performs preprocessing, feature extraction and classification. In the earlier stage, median filtering (MF) technique is applied to preprocess the input image. Next, convolutional neural network (CNN) based VGGNet-19 model is applied as a feature extractor. At last, artificial neural network (ANN) is employed as a classification model to identify and classify the existence of COVID-19. An extensive set of simulation analysis takes place to ensure the superior performance of the applied model. The outcome of the experiments showcased the betterment interms of different measures.