Enhanced Pneumonia Detection in Chest X-Rays Based on Integrated Denoising Autoencoders and Convolutional Neural Networks

Yufeng Xia

2024

Abstract

This research presents a new hybrid model that improves pneumonia detection from chest X-ray images by combining denoising autoencoders (DAEs) with convolutional neural networks (CNNs). The model concurrently performs image denoising and disease classification, leveraging both processes to enhance diagnostic accuracy. Preprocessing steps for the Chest X-Ray Images (Pneumonia) dataset included resizing to 150x150 pixels, image augmentation, and normalization to facilitate effective training. The integrated model architecture uses CNNs for feature extraction and classification, paired with DAEs for image denoising, all implemented using TensorFlow and optimized with the Adam optimizer on an NVIDIA RTX 4080 GPU. This setup allows dynamic adjustments of the learning rate, improving performance metrics. The model achieved a peak validation accuracy of 98.4% and demonstrated a substantial reduction in image noise, evidenced by a low Mean Squared Error (MSE) of 0.0049. These results highlight the model's capability to deliver precise classifications and superior image quality, thus enabling more reliable diagnoses. This study points to the potential for applying such integrated models more broadly in medical imaging, enhancing both interpretability and reliability of automated medical diagnostics. Future efforts will aim to extend this model's application to additional medical conditions and enhance its robustness and generalizability.

Paper Citation

in Harvard Style

Xia Y. (2024). Enhanced Pneumonia Detection in Chest X-Rays Based on Integrated Denoising Autoencoders and Convolutional Neural Networks. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 799-803. DOI: 10.5220/0012973600004508

in Bibtex Style

@conference{emiti24,
author={Yufeng Xia},
title={Enhanced Pneumonia Detection in Chest X-Rays Based on Integrated Denoising Autoencoders and Convolutional Neural Networks},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={799-803},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012973600004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Enhanced Pneumonia Detection in Chest X-Rays Based on Integrated Denoising Autoencoders and Convolutional Neural Networks
SN - 978-989-758-713-9
AU - Xia Y.
PY - 2024
SP - 799
EP - 803
DO - 10.5220/0012973600004508
PB - SciTePress