Statistical analysis of structural changes in whole brain based on nonlinear image registration
Research output: Contribution to journal › Conference article › Contributed › peer-review
Contributors
Abstract
This paper describes a new method for detecting structural brain differences based on the analysis of deformation fields. Deformations are obtained by a 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).
Details
Original language | English |
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Pages (from-to) | 794-801 |
Number of pages | 8 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 3661 |
Issue number | II |
Publication status | Published - 1999 |
Peer-reviewed | Yes |
Conference
Title | Proceedings of the 1999 Medical Imaging - Image Processing |
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Duration | 22 - 25 February 1999 |
City | San Diego, CA, USA |