White matter tractographies registration using Gaussian mixture modeling

Orly Zvitia, Arnaldo Mayer, Hayit Greenspan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


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.

Original languageEnglish
Title of host publicationMedical Imaging 2008
Subtitle of host publicationImage Processing
StatePublished - 2008
Externally publishedYes
EventMedical Imaging 2008: Image Processing - San Diego, CA, United States
Duration: 17 Feb 200819 Feb 2008

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceMedical Imaging 2008: Image Processing
Country/TerritoryUnited States
CitySan Diego, CA


  • Gaussian mixture model
  • Mean-shift
  • Region-of-interest
  • Registration
  • Tractography
  • White matter


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