OCTA Image-Based Machine Learning Models for Discriminating Alzheimer’s Disease from Neurodegenerative and Ocular Conditions

Cunyi Xu

2025

Abstract

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that poses a significant challenge, particularly as the global population ages. Timely diagnosis is crucial for managing AD, and this study aims to contribute to early detection by analyzing Optical Coherence Tomography Angiography (OCTA) images using machine learning models. In this work, we leverage the structural and functional connections between the eye and brain to enhance the discrimination of AD from other neurodegenerative and ocular conditions. We also compiled a comprehensive dataset of OCTA images from various imaging devices, representing a range of diseases. Using a pre-trained nnU-Net, we segmented vascular structures and calculated vascular density metrics, while also extracting histogram and Gray-Level Co-occurrence Matrix (GLCM) features for texture analysis. Various machine learning models were trained and evaluated through five-fold cross-validation, with the Random Forest model achieving 78.15% accuracy in classifying multi-disease OCTA images. The model exhibited high recall for stroke, diabetes, and age-related macular degeneration, but lower recall for AD, congenital heart disease, and hypertension, indicating potential misclassification. Our findings emphasize the utility of OCTA imaging and machine learning for early AD diagnosis, paving the way for future research to refine image processing and classification methods.

Paper Citation

in Harvard Style

Xu C. (2025). OCTA Image-Based Machine Learning Models for Discriminating Alzheimer’s Disease from Neurodegenerative and Ocular Conditions. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING; ISBN 978-989-758-731-3, SciTePress, pages 324-331. DOI: 10.5220/0013141300003911

in Bibtex Style

@conference{bioimaging25,
author={Cunyi Xu},
title={OCTA Image-Based Machine Learning Models for Discriminating Alzheimer’s Disease from Neurodegenerative and Ocular Conditions},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING},
year={2025},
pages={324-331},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013141300003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOIMAGING
TI - OCTA Image-Based Machine Learning Models for Discriminating Alzheimer’s Disease from Neurodegenerative and Ocular Conditions
SN - 978-989-758-731-3
AU - Xu C.
PY - 2025
SP - 324
EP - 331
DO - 10.5220/0013141300003911
PB - SciTePress