Application of deep learning in chest X-ray abnormality detection

Authors

  • Nhan Ngo
  • Toi Vo
  • Lua Ngo*

Abstract

Lung diseases are the most common diseases worldwide, especially in Vietnam. Certain thoracic lung diseases can even lead to dangerous conditions for patients. X-ray are a useful imaging modality for detecting the abnormalities in the chest area. Furthermore, artificial intelligence can improve the detection of abnormalities in X-ray images, reduce misdiagnosis, close the knowledge gap between doctors, and alleviate the pressure on doctors. Therefore, this study aims to apply deep learning techniques to detect abnormalities in chest X-ray images and use data science and statistical approaches to improve the performance of the deep learning model. The data was explored and processed to obtain high quality data with optimal characteristics. We then applied data augmentation and optimization to the RetinaNet model with ResNet101 in a Feature Pyramid Network (FPN) backbone to achieve the best performance. Our model achieved mean average precision of 0.55 at a threshold of 0.5 (mAP@0.5) in a validation set, which included five diseases: aortic enlargement, cardiomegaly, interstitial lung disease, infiltration, and nodule/mass.

Keywords:

deep learning, RetinaNet model, thoracic lung diseases, X-ray

DOI:

https://doi.org/10.31276/VJSTE.65(4).84-93

Classification number

3.2, 3.6

Author Biographies

Nhan Ngo

School of Biomedical Engineering, International University, Vietnam National University - Ho Chi Minh City,
Quarter 6, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam

Vietnam National University - Ho Chi Minh City, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam

Toi Vo

School of Biomedical Engineering, International University, Vietnam National University - Ho Chi Minh City,
Quarter 6, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam

Vietnam National University - Ho Chi Minh City, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam

Lua Ngo

School of Biomedical Engineering, International University, Vietnam National University - Ho Chi Minh City,
Quarter 6, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam

Vietnam National University - Ho Chi Minh City, Linh Trung Ward, Thu Duc City, Ho Chi Minh City, Vietnam

Downloads

Published

2023-12-15

Received 19 September 2022; revised 27 November 2022; accepted 2 December 2022

How to Cite

Nhan Ngo, Toi Vo, & Lua Ngo. (2023). Application of deep learning in chest X-ray abnormality detection. Vietnam Journal of Science, Technology and Engineering, 65(4), 84-93. https://doi.org/10.31276/VJSTE.65(4).84-93

Issue

Section

Life Sciences