Paper
21 May 1999 Statistical analysis of structural changes in a whole brain based on nonlinear image registration
Christian Gaser, Stefan Kiebel, Stefan Riehemann, Hans-Peter Volz, Heinrich Sauer
Author Affiliations +
Abstract
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).
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christian Gaser, Stefan Kiebel, Stefan Riehemann, Hans-Peter Volz, and Heinrich Sauer "Statistical analysis of structural changes in a whole brain based on nonlinear image registration", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); https://doi.org/10.1117/12.348636
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Cited by 1 scholarly publication.
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KEYWORDS
Brain

Statistical analysis

Image registration

Control systems

Neuroimaging

Statistical modeling

Transform theory

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