Abstract
Mild cognitive impairment (MCI) is recognized as a precursor to Alzheimer's disease (AD), a progressive and irreversible neurodegenerative disorder of the brain. The neurodegeneration of brain connectivity networks plays a pivotal role in the development and progression of MCI. Traditionally, brain networks are generated using coarse-grained brain regions, where the regions serve as nodes and their functional or structural connections are used as edges. Recently, a novel finer scale brain folding patterns named 3hinge gyrus (3HG) was identified, which is defined as the conjunctions coming from three directions on gyral crests. 3HGs have been shown playing an important role in brain network and can serve as hubs. In this study, our objective is to construct a novel 3HG-based finer-scale brain connectome and comprehensively compare its performance with traditional region-based connectome in predicting MCI against Normal Controls (NC). The results of extensive experiments demonstrate the superior performance of 3HG-based brain connectome, shedding light on the potential of 3HG-based connectomes in capturing intricate neurodegenerative patterns associated with MCI and AD.
Recommended Citation
Y. Lyu et al., "Mild Cognitive Impairment Classification Using A Novel Finer-Scale Brain Connectome," Proceedings International Symposium on Biomedical Imaging, Institute of Electrical and Electronics Engineers, Jan 2024.
The definitive version is available at https://doi.org/10.1109/ISBI56570.2024.10635558
Department(s)
Computer Science
Keywords and Phrases
3HG; finer-scale brain-connectome; MCI
International Standard Serial Number (ISSN)
1945-8452; 1945-7928
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2024

Comments
National Institutes of Health, Grant R01AG075582