Empirical Evaluation of Covariance Estimates for Mutual Information Coregistration

MICCAI 2004 Rennes/St. Malo, France.

Mutual information has become a popular similarity measure in multi-modality medical image registration since it was first applied to the problem in 1995. This paper describes a method for calculating the covariance matrix for mutual information coregistration. We derive an expression for the matrix through identification of mutual information with a log-likelihood measure. The validity of this result is then demonstrated through comparison with the results of Monte-Carlo simulations of the coregistration of T1-weighted to T2-weighted synthetic and genuine MRI scans of the brain. We conclude with some observations on the theoretical basis of the mutual information measure as a log-likelihood.

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