Structure-specific statistical mapping of white matter tracts using the continuous medial representation

Paul A. Yushkevich, Hui Zhang, Tony J Simon, James C. Gee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE International Conference on Computer Vision
DOIs
Publication statusPublished - 2007
Event2007 IEEE 11th International Conference on Computer Vision, ICCV - Rio de Janeiro, Brazil
Duration: Oct 14 2007Oct 21 2007

Other

Other2007 IEEE 11th International Conference on Computer Vision, ICCV
CountryBrazil
CityRio de Janeiro
Period10/14/0710/21/07

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ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Yushkevich, P. A., Zhang, H., Simon, T. J., & Gee, J. C. (2007). Structure-specific statistical mapping of white matter tracts using the continuous medial representation. In Proceedings of the IEEE International Conference on Computer Vision [4409169] https://doi.org/10.1109/ICCV.2007.4409169