Morphological Factor Estimation via High-Dimensional Reduction: Prediction of MCI Conversion to Probable AD release_vaxrlvv345fb3kciyuy727lpgu

by Simon Duchesne, Abderazzak Mouiha

Published in International Journal of Alzheimer's Disease by Hindawi Limited.

2011   Volume 2011, p1-8

Abstract

We propose a novel morphological factor estimate from structural MRI for disease state evaluation. We tested this methodology in the context of Alzheimer's disease (AD) with 349 subjects. The method consisted in (a) creating a reference MRI feature eigenspace using intensity and local volume change data from 149 healthy, young subjects; (b) projecting MRI data from 75 probable AD, 76 controls (CTRL), and 49 Mild Cognitive Impairment (MCI) in that space; (c) extracting high-dimensional discriminant functions; (d) calculating a single morphological factor based on various models. We used this methodology in leave-one-out experiments to (1) confirm the superiority of an inverse-squared model over other approaches; (2) obtain accuracy estimates for the discrimination of probable AD from CTRL (90%) and the prediction of conversion of MCI subjects to probable AD (79.4%).
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Type  article-journal
Stage   published
Year   2011
Language   en ?
DOI  10.4061/2011/914085
PubMed  21755033
PMC  PMC3132989
Wikidata  Q42792695
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