The fiber tracts generated using diffusion MRI are usually simply displayed and assessed visually for a specific clinical or medical research purpose. This paper proposes computational techniques that can be used to study the shape of the tracts and make interindividual comparisons. These methods make use of fundamental geometric invariants, such as curvatures and torsions, or Fourier descriptors, together with the link of a pair of curves. Intersubject comparisons only require that the starting and ending points of the tracts can be defined and do not require point-by-point correspondences such as obtained using image registration. Principal component analysis-based shape analysis is also investigated. The invariants are tested on simulations and in vivo datasets, and the scale dependence and noise sensitivity of the measures are assessed. The potential for these techniques to be used in neuroscience research and clinical applications is demonstrated.
(c) 2006 Wiley-Liss, Inc.