Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging
Abstract
The statistical analysis of covariance matrix data is considered and, in particular, methodology is discussed which takes into account the non-Euclidean nature of the space of positive semi-definite symmetric matrices. The main motivation for the work is the analysis of diffusion tensors in medical image analysis. The primary focus is on estimation of a mean covariance matrix and, in particular, on the use of Procrustes size-and-shape space....
Paper Details
Title
Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging
Published Date
Sep 30, 2009
Volume
3
Issue
3
Pages
1102 - 1123
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