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Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
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Abstract

Introduction

This paper presents a multichannel deep-learning method for detecting lung diseases using chest X-ray images. Using EfficientNetB0 through EfficientNetB7 pretrained models, the methodology offers improved performance in classifying COVID-19, viral pneumonia, and normal chest X-rays.

Methods

The EfficientNetB2 model was customized by incorporating Squeeze-and-Excitation (SE) blocks and the Convolutional Block Attention Module (CBAM) to improve the model's attention mechanisms. Additional convolutional layers were added for improved feature extraction, and multi-scale feature fusion was implemented to capture features at different scales.

Results

In this study, 99.3% of the unseen chest X-ray images were identified using the proposed model. It demonstrated superior performance, surpassing existing techniques and highlighting its robustness and generalizability on unseen data samples.

Conclusion

Moreover, visualization techniques were used to inspect the intermediate layers of the model, providing deeper insights into its processing and interpretation of medical images. The proposed method offers healthcare radiologists a valuable tool for rapid and accurate point of care diagnoses.

© 2024 The Author(s). Published by Bentham Science Publisher.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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2024-01-01
2025-06-26

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/content/journals/cmir/10.2174/0115734056344651241023070250
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Advanced Lung Disease Detection: CBAM-Augmented, Lightweight EfficientNetB2 with Visual Insights
Curr. Med. Imaging 20, e15734056344651 (2024); https://doi.org/10.2174/0115734056344651241023070250
/content/journals/cmir/10.2174/0115734056344651241023070250
/content/journals/cmir/10.2174/0115734056344651241023070250
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  • Article Type:     Research Article
Keyword(s): Chest X-ray images; COVID-19; EfficientNet; Feature extraction; Lung disease detection; Viral pneumonia

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