Title :
Structure-Specific Statistical Mapping of White Matter Tracts using the Continuous Medial Representation
Author :
Yushkevich, Paul A. ; Zhang, Hui ; Simon, Tony J. ; Gee, James C.
Author_Institution :
Univ. of Pennsylvania, Philadelphia
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.
Keywords :
image representation; statistical analysis; tensors; continuous medial representation; diffusion tensor images; diffusion-based white matter studies; normalization algorithm; pediatric chromosome deletion syndrome; structure-specific statistical mapping; tensor-based features; tract-based spatial statistics; Anatomical structure; Biological cells; Data visualization; Laboratories; Performance analysis; Skeleton; Smoothing methods; Solid modeling; Statistical analysis; Tensile stress;
Conference_Titel :
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location :
Rio de Janeiro
Print_ISBN :
978-1-4244-1630-1
Electronic_ISBN :
1550-5499
DOI :
10.1109/ICCV.2007.4409169