From NAMIC Wiki
Revision as of 17:52, 26 November 2012 by Manasi (talk | contribs) (→‎Publications)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search
Home < Projects:MixedEffectsShape
Back to Utah Algorithms

Mixed-Effects Shape Models for Longitudinal Analysis

Visualization of fixed- and random-effects for brain surfaces.


We propose a new method for longitudinal shape analysis that fits a linear mixed-effects model, while simultaneously optimizing correspondences on a set of anatomical shapes. Shape changes are modeled in a hierarchical fashion, with the global population trend as a fixed effect and individual trends as random effects. The statistical significance of the estimated trends are evaluated using specifically designed permutation tests. We also develop a permutation test based on the Hotelling T2 statistic to compare the average shapes trends between two populations. We demonstrate the benefits of our method on a synthetic example of longitudinal tori and data from a developmental neuroimaging study.

Key Investigators

  • Utah: Manasi Datar, Prasanna Muralidharan, Sylvain Gouttard, Guido Gerig, Ross Whitaker and P. Thomas Fletcher