COVID-19 Detection from Chest X-Ray Images Using CNNs Models: Further Evidence from Deep Transfer Learning

Mohamed Samir Boudrioua

doi:10.2139/ssrn.3630150

Abstract

In this study we revisit the identification of COVID-19 from chest x-ray images using Deep Learning. We collect a relatively large COVID-19 dataset comparing with previous studies that contains 309 real COVID-19 chest x-ray images. We prepare also 2000 chest x-ray images of pneumonia cases and 1000 images of healthy chest cases. Deep Transfer Learning is used to detect abnormalities in our images dataset. We fine-tune three pre-trained deep convolutional neural networks (CNNs) models on a training dataset; DenseNet 121, NASNetLarge and NASNetMobile. The evaluation of our models on a test dataset shows that these models achieve a sensitivity rate of around 99.45 % on average, and a specificity rate of around 99.5 % on average. These results could be helpful for an automatic diagnosis of COVID-19 infections, but the clinical diagnosis stills 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

Introduction

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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Results

Conclusion