Abstract
Introduction: The early automatic diagnosis of the novel coronavirus (COVID-19) disease could be very helpful to reduce its spread around the world. In this study, we revisit the identification of COVID-19 from chest X-ray images using deep learning. Methods: We collected a relatively large COVID-19 dataset—compared with previous studies—containing 309 real COVID-19 chest X-ray images. We also prepared 2,000 chest X-ray images of pneumonia cases and 1,000 images of healthy controls. Deep transfer learning was used to detect abnormalities in our image dataset. We fine-tuned three, pre-trained convolutional neural network (CNN) models on a training dataset: DenseNet 121, NASNetLarge, and NASNet-Mobile. Results: The evaluation of our models on a test dataset showed that these models achieved an average sensitivity rate of approximately 99.45% and an average specificity rate of approximately 99.5%. Conclusion: A larger dataset of COVID-19 X-ray images could lead to more accurate and reliable identification of COVID-19 infections using deep transfer learning. However, the clinical diagnosis of COVID-19 disease is always necessary.
Highlights
The early automatic diagnosis of the novel coronavirus (COVID-19) disease could be very helpful to reduce its spread around the world
Datasets A total of 309 COVID-19 chest X-ray images are collected; 236 COVID-19 images are obtained from the datasets of Cohen et al [7,8] and 73 other COVID-19 images are obtained from Kaggle dataset
Models The Deep Transfer Learning method is used in this study, because the samples in our datasets are small and not sufficient to train a convolutional neural networks (CNNs) model from onset. [2,4,5] Transfer learning consists of extracting features learned on one problem, and using them on a new, similar problem
Summary
The early automatic diagnosis of the novel coronavirus (COVID-19) disease could be very helpful to reduce its spread around the world. We revisit the identification of COVID-19 from chest X-ray images using Deep Learning. [1,2,3] The early automatic diagnosis of this disease may be very beneficial for reducing its spread. [4] Deep Learning is one artificial intelligence method that can be helpful in detecting COVID-19 infections from medical images such as X-ray images, when we have a small image dataset. “COVID-19 Detection from Chest X-Ray Images Using CNNs Models: Further Evidence from Deep Transfer Learning,” The University of Louisville Journal of Respiratory Infections: Vol 4, Iss. 1, Article 53.
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