title: Multi-scale characterization of white matter tract geometry.
abstract: The geometry of white matter tracts is of increased interest for a variety of neuroscientific investigations, as it is a feature reflective of normal neurodevelopment and disease factors that may affect it. In this paper, we introduce a novel method for computing multi-scale fibre tract shape and geometry based on the differential geometry of curve sets. By measuring the variation of a curve's tangent vector at a given point in all directions orthogonal to the curve, we obtain a 2D "dispersion distribution function" at that point. That is, we compute a function on the unit circle which describes fibre dispersion, or fanning, along each direction on the circle. Our formulation is then easily incorporated into a continuous scale-space framework. We illustrate our method on different fibre tracts and apply it to a population study on hemispheric lateralization in healthy controls. We conclude with directions for future work.
authors.affiliation: Laboratory for Mathematics in Imaging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Peter
authors.initials: P
authors.lastname: Savadjiev
authors.forename: Yogesh
authors.initials: Y
authors.lastname: Rathi
authors.forename: Sylvain
authors.initials: S
authors.lastname: Bouix
authors.forename: Ragini
authors.initials: R
authors.lastname: Verma
authors.forename: Carl-Fredrik
authors.initials: CF
authors.lastname: Westin
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D063132:Connectome / Q000379:methods*; D044962:Data Compression / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity