Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging

Volume: 3, Issue: 3, Pages: 1102 - 1123
Published: Sep 30, 2009
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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