Power Euclidean metrics for covariance matrices with application to diffusion tensor imaging
Power Euclidean metrics for covariance matrices with application to diffusion tensor imaging
复制标题
协方差矩阵的幂欧几里得度量及其在扩散张量成像中的应用
DOI：
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发表时间：
2010
期刊：
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通讯作者：
J. Peyrat
中科院分区：
文献类型：
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作者：
I. Dryden;X. Pennec;J. Peyrat
Various metrics for comparing diffusion tensors have been recently proposed in the literature. We consider a broad family of metrics which is indexed by a single power parameter. A likelihood-based procedure is developed for choosing the most appropriate metric from the family for a given dataset at hand. The approach is analogous to using the Box-Cox transformation that is frequently investigated in regression analysis. The methodology is illustrated with a simulation study and an application to a real dataset of diffusion tensor images of canine hearts.
