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Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network

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Abbas, Asmaa, Abdelsamea, Mohammed M., Gaber, Mohamed Medhat·2021·Applied Intelligence
DOI 10.1007/s10489-020-01829-7

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Abstract

Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural networks ( CNN s) for image recognition and classification. However, due to the limited availability of annotated medical images, the classification of medical images remains the biggest challenge in medical diagnosis. Thanks to transfer learning, an effective mechanism that can provide a promising solution by transferring knowledge from generic object recognition tasks to domain-specific tasks. In this paper, we validate and a deep CNN , called Decompose, Transfer, and Compose ( DeTraC ), for the classification of COVID-19 chest X-ray images. DeTraC can deal with any irregularities in the image dataset by investigating its class boundaries using a class decomposition mechanism. The experimental results showed the capability of DeTraC in the detection of COVID-19 cases from a comprehensive image dataset collected from several hospitals around the world. High accuracy of 93.1% (with a sensitivity of 100%) was achieved by DeTraC in the detection of COVID-19 X-ray images from normal, and severe acute respiratory syndrome cases.

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Cited by

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Metadata

Authors
Abbas, A., Abdelsamea, M. M., & Gaber, M. M.
Venue
Applied Intelligence
Publisher
Springer Science and Business Media LLC
Published
2020-09-05
Volume
51
Issue
2
Pages
854-864
ISSN
  • 0924-669X (ISSN-L)
  • 1573-7497
DOI
10.1007/s10489-020-01829-7
OpenAlex
W3014890122
Cited by
1,124
References
11
FWCI
103.32
Type
journal article
Language
en
Open access
hybrid
Licence

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CoChat. (2026). Citation check: Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network. https://app.cochat.ai/papers/10.1007/s10489-020-01829-7
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Abbas, A., Abdelsamea, M. M., & Gaber, M. M. (2021). Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network. Applied Intelligence. https://doi.org/10.1007/s10489-020-01829-7

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