Lung Inflammatory Classification of Diseases using X-ray Images

Abstract

Recently, studies in inflammatory diseases categorization become of interest in the research community, especially with the sudden outbreak of the Covid-19 virus. Transfer learning proved to be the state-of-the-art when it comes to image classification problems, or related tasks. These methods achieve good results in this type of applications. Lately, this pre-trained embedding became even popular due to X-ray related studies for early Covid-19 diagnosis. In this study, we investigate the X-ray image classification problem using the transfer learning method. We fine-tuned and trained our model using pre-trained models such as AlexNet, VGG16, DenseNet etc, and a baseline deep neural network. We then evaluated this model in terms of classification evaluation metrics. The study shows that DenseNet achieves high accuracy compared to the other pre-trained and baseline CNN models.