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Statistical analysis of structural changes in a whole brain based on nonlinear image registration

This paper describes a new method for detecting structural brain differences based on the analysis of deformation fields. Deformations are obtained by an intensity-based nonlinear registration routine which transforms one brain onto another one. We present a general multivariate statistical approach to analyze deformation fields in different subjects. This multivariate general linear model provides the implementation of most forms of experimental designs. We apply our method to the brains of 85 schizophrenic patients and 75 healthy volunteers to examine, whether low frequency deformations are sufficiently sensitive to detect regional deviations in the brains of both groups. We demonstrate the application of the multivariate general linear model to a subtractive (modeling group differences) and a parametric design (testing a linear relationship between one variable and the deformation field).