Smooth Normative Brain Mapping of Three-Dimensional Morphometry Imaging Data Using Skew-Normal Regression.

ABSTRACT: Tensor-based morphometry (TBM) aims at showing local differences in brain volumes with respect to a common template. TBM images are smooth, but they exhibit (especially in diseased groups) higher values in some brain regions called lateral ventricles. More specifically, our voxelwise analysis shows both a mean-variance relationship in these areas and evidence of spatially dependent skewness. We propose a model for three-dimensional imaging data where mean, variance and skewness functions vary smoothly across brain locations. We model the voxelwise distributions as skew-normal. We illustrate an interpolation-based approach to obtain smooth parameter functions based on a subset of voxels. The effects of age and sex are estimated on a reference population of cognitively normal subjects from t

SUBMITTER: Palma M 

PROVIDER: S-EPMC11875072 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature