MCI classification based on fusion of brain network properties and local cortex signal features

Yu Changyuan; Miao Song; Fei Han

doi:10.1117/12.2640806

3 October 2022 MCI classification based on fusion of brain network properties and local cortex signal features

Yu Changyuan, Miao Song, Fei Han

Proceedings Volume 12290, International Conference on Computer Network Security and Software Engineering (CNSSE 2022); 1229013 (2022) https://doi.org/10.1117/12.2640806
Event: International Conference on Computer Network Security and Software Engineering (CNSSE 2022), 2022, Zhuhai, China

Abstract

Machine learning and pattern recognition have been widely used in resting-state functional magnetic resonance imaging (rs-fMRI) data to investigate Alzheimer’s disease (AD). However, many previous methods have not focused on the pre-Alzheimer's disease, mild cognitive impairment (MCI), have mostly classified features from functional separation or functional integration alone, which may have overlooked the correlation between the two. We propose a novel method for MCI diagnosis using the fusion local features of brain area signals as features for functional separation and brain network properties as features for functional integration. The rs-fMRI data of 43 MCI patients and 46 normal cognitive (NC) controls were analyzed using graph theory and nonlinear time series analysis to extract the brain network properties and local cortex signal features. The classifier-SVM achieved an accuracy of 92.8% based on the above features, which is generally higher than those of conventional methods based on functional integration using brain network properties alone or functional separation using local features alone. Our method demonstrates the measure of multi-feature integration of functional integration and functional separation as a powerful tool to classify MCI patients.

Citation Download Citation

Yu Changyuan, Miao Song, and Fei Han "MCI classification based on fusion of brain network properties and local cortex signal features", Proc. SPIE 12290, International Conference on Computer Network Security and Software Engineering (CNSSE 2022), 1229013 (3 October 2022); https://doi.org/10.1117/12.2640806

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available