COVID-19 x-ray image detection algorithm based on deep learning

Bo Yin

doi:10.1117/12.2671199

28 April 2023 COVID-19 x-ray image detection algorithm based on deep learning

Bo Yin

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 1261026 (2023) https://doi.org/10.1117/12.2671199
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

In order to enhance the ability to diagnose and distinguish COVID-19 from ordinary pneumonia, and to assist medical staff in chest x-ray detection of pneumonia patients, this paper proposes a COVID-19 x-ray image detection algorithm based on deep learning network. First of all, a model of deep learning network is set up based on VGG - 16, and then, the network structure and parameter optimization is adjusted, which makes the network model can be applied to COVID-19 x-ray imaging detection task. In the end, through adjusting the image size of the original data set, the input data meets the requirements of the deep learning network. Experimental results show that the proposed algorithm can effectively learn the characteristics of the COVID-19 x-ray image data set and accurately detect three states of COVID-19, common viral pneumonia and non-pneumonia, with a very high detection accuracy of 95.8%.

Citation Download Citation

Bo Yin "COVID-19 x-ray image detection algorithm based on deep learning", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 1261026 (28 April 2023); https://doi.org/10.1117/12.2671199

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KEYWORDS

COVID 19

Deep learning

X-ray imaging

Education and training

X-rays

Convolution

Image classification

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