Structure-specific statistical mapping of white matter tracts using the continuous medial representation.
Proceedings of the IEEE International Conference on Computer Vision.
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. ©2007 IEEE.
|Title:||Structure-specific statistical mapping of white matter tracts using the continuous medial representation|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science > Computer Science|
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