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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Mixed-Effects Shape Models for Estimating Longitudinal Changes in Anatomy
verfasst von : Manasi Datar, Prasanna Muralidharan, Abhishek Kumar, Sylvain Gouttard, Joseph Piven, Guido Gerig, Ross Whitaker, P. Thomas Fletcher
Erschienen in: Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data
Verlag: Springer Berlin Heidelberg
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In this paper, 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
T
2
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.