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Structure-Specific Statistical Mapping of White Matter Tracts using the Continuous Medial Representation

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4 Author(s)
Yushkevich, P.A. ; Univ. of Pennsylvania, Philadelphia ; Hui Zhang ; Simon, T.J. ; Gee, J.C.

This paper describes a new statistical analysis framework for diffusion-based white matter studies. The framework is based on a recent unbiased normalization algorithm for diffusion tensor images. Taking advantage of the fact that most human white matter tracts are thin sheet-like structures, this framework uses deformable medial models to represent six of the major tracts in a white matter atlas derived for a given set of images. The medial representation allows one to average tensor-based features along directions perpendicular to the tracts, thus reducing data dimensionality and accounting for errors in normalization. Unlike earlier work in the area of tract-based spatial statistics (Smith et al, 2006), this framework enables the analysis of individual white matter structures, and provides a range of possibilities for computing statistics and visualizing differences between cohorts. The framework is demonstrated in a study of white matter differences in pediatric chromosome 22q deletion syndrome.

Published in:

Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on

Date of Conference:

14-21 Oct. 2007