Multivariate Statistical Analysis of Deformation Momenta Relating Anatomical Shape to Neuropsychological Measures

被引：0

作者：

Singh, Nikhil ^{[1
]}

Fletcher, P. Thomas ^{[1
]}

Preston, J. Samuel ^{[1
]}

Ha, Linh ^{[1
]}

King, Richard ^{[1
]}

Marron, J. Stephen ^{[2
]}

Wiener, Michael ^{[3
]}

Joshi, Sarang ^{[1
]}

机构：

[1] Univ Utah, Salt Lake City, UT 84112 USA

[2] Univ North Carolina Chapel Hill, Chapel Hill, NC USA

[3] Univ Calif San Francisco, San Francisco, CA USA

来源：

MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2010, PT III | 2010年 / 6363卷

基金：

美国国家科学基金会; 美国国家卫生研究院;

关键词：

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

The purpose of tins study is to characterize the neuroanatomical variations observed in neurological disorders such as dementia. We do a global statistical analysis of brain anatomy and identify the relevant shape deformation patterns that explain corresponding variations in clinical neuropsychological measures. The motivation is to model the inherent relation between anatomical shape and clinical measures and evaluate its statistical significance. We use Partial Least Squares for the multivariate statistical analysis of the deformation momenta, under the Large Deformation Diffeomorphic framework. The statistical methodology extracts pertinent directions in the momenta space and the clinical response space in terms of latent variables. We report the results of this analysis on 313 subjects from the Mild Cognitive Impairment; group in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

引用

页码：529 / +

页数：3

共 25 条

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