@inproceedings{4e6550cd900740e0bc004ba3fad2186b,
title = "Boosting classification accuracy of diffusion MRI derived brain networks for the subtypes of mild cognitive impairment using higher order singular value decomposition",
abstract = "Mild cognitive impairment (MCI) is an intermediate stage between normal aging and Alzheimer's disease (AD), and around 10-15% of people with MCI develop AD each year. More recently, MCI has been further subdivided into early and late stages, and there is interest in identifying sensitive brain imaging biomarkers that help to differentiate stages of MCI. Here, we focused on anatomical brain networks computed from diffusion MRI and proposed a new feature extraction and classification framework based on higher order singular value decomposition and sparse logistic regression. In tests on publicly available data from the Alzheimer's Disease Neuroimaging Initiative, our proposed framework showed promise in detecting brain network differences that help in classifying early versus late MCI.",
keywords = "Mild Cognitive Impairment, brain network, classification, diffusion MRI, high order SVD",
author = "L. Zhan and Y. Liu and J. Zhou and J. Ye and Thompson, {P. M.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",
year = "2015",
month = jul,
day = "21",
doi = "10.1109/ISBI.2015.7163833",
language = "English (US)",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "131--135",
booktitle = "2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015",
}