White matter tractographies registration using Gaussian mixture modeling

This paper proposes a novel and robust approach to the registration (matching) of intra-subject white matter (WM) fiber sets extracted from DT-MRI scans by Tractography. For each fiber, a feature space representation is obtained by appending the sequence of its 3D coordinates. Clustering by non-parametric adaptive mean shift provides a representative fiber for each cluster hereafter termed the fiber-mode (FM). For each FM, the parameters of a multivariate Gaussian are computed from its fiber population, leading to a mixture of Gaussians (MoG) for the whole fiber set. The number of Gaussians used for a fiber set equals the number of FM representing the set. The alignment of two fiber sets is then treated as the alignment between two MoGs, and is solved by maximizing the correlation ratio between them. Initial results are presented for real intrasubject fiber sets and synthetic transformations.