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Hierarchical Anatomical Brain Networks For Mci Prediction By Partial Least Square Analysis, Luping Zhou, Yaping Wang, Yang Li, Pew-Thian Yap, Dinggang Shen

Faculty of Engineering and Information Sciences - Papers: Part A

Owning to its clinical accessibility, T1-weighted MRI has been extensively studied for the prediction of mild cognitive impairment (MCI) and Alzheimer's disease (AD). The tissue volumes of GM, WM and CSF are the most commonly used measures for MCI and AD prediction. We note that disease-induced structural changes may not happen at isolated spots, but in several inter-related regions. Therefore, in this paper we propose to directly extract the inter-region connectivity based features for MCI prediction. This involves constructing a brain network for each subject, with each node representing an ROI and each edge representing regional interactions. This network is …