title: White matter bundle registration and population analysis based on Gaussian processes.
abstract: This paper proposes a method for the registration of white matter tract bundles traced from diffusion images and its extension to atlas generation, Our framework is based on a Gaussian process representation of tract density maps. Such a representation avoids the need for point-to-point correspondences, is robust to tract interruptions and reconnections and seamlessly handles the comparison and combination of white matter tract bundles. Moreover, being a parametric model, this approach has the potential to be defined in the Gaussian processes' parameter space, without the need for resampling the fiber bundles during the registration process. We use the similarity measure of our Gaussian process framework, which is in fact an inner product, to drive a diffeomorphic registration algorithm between two sets of homologous bundles which is not biased by point-to-point correspondences or the parametrization of the tracts. We estimate a dense deformation of the underlying white matter using the bundles as anatomical landmarks and obtain a population atlas of those fiber bundles. Finally we test our results in several different bundles obtained from in-vivo data.
authors.affiliation: Laboratory of Mathematics in Imaging, Brigham & Women's Hospital, Boston, MA, USA.
authors.forename: Demian
authors.initials: D
authors.lastname: Wassermann
authors.forename: Yogesh
authors.initials: Y
authors.lastname: Rathi
authors.forename: Sylvain
authors.initials: S
authors.lastname: Bouix
authors.forename: Marek
authors.initials: M
authors.lastname: Kubicki
authors.forename: Ron
authors.initials: R
authors.lastname: Kikinis
authors.forename: Martha
authors.initials: M
authors.lastname: Shenton
authors.forename: Carl-Fredrik
authors.initials: CF
authors.lastname: Westin
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D003198:Computer Simulation; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique