General multivariate linear modeling of surface shapes using SurfStat.
General multivariate linear modeling of surface shapes using SurfStat.
复制标题
使用 SurfStat 对表面形状进行一般多元线性建模。
DOI：
10.1016/j.neuroimage.2010.06.032
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发表时间：
2010-11-01
期刊：
影响因子：
5.7
通讯作者：
Davidson, Richard J.
中科院分区：
文献类型：
--
作者：
Chung, Moo K.;Worsley, Keith J.;Nacewicz, Brendon M.;Dalton, Kim M.;Davidson, Richard J.
Although there are many imaging studies on traditional ROI-based amygdala volumetry, there are very few studies on modeling amygdala shape variations. This paper present a unified computational and statistical framework for modeling amygdala shape variations in a clinical population. The weighted spherical harmonic representation is used as to parameterize, to smooth out, and to normalize amygdala surfaces. The representation is subsequently used as an input for multivariate linear models accounting for nuisance covariates such as age and brain size difference using SurfStat package that completely avoids the complexity of specifying design matrices. The methodology has been applied for quantifying abnormal local amygdala shape variations in 22 high functioning autistic subjects.
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