Improved tractography alignment using combined volumetric and surface registration

Neuroimage. 2010 May 15;51(1):206-13. doi: 10.1016/j.neuroimage.2010.01.101. Epub 2010 Feb 12.


Previously we introduced an automated high-dimensional non-linear registration framework, CVS, that combines volumetric and surface-based alignment to achieve robust and accurate correspondence in both cortical and sub-cortical regions (Postelnicu et al., 2009). In this paper we show that using CVS to compute cross-subject alignment from anatomical images, then applying the previously computed alignment to diffusion weighted MRI images, outperforms state-of-the-art techniques for computing cross-subject alignment directly from the DWI data itself. Specifically, we show that CVS outperforms the alignment component of TBSS in terms of degree-of-alignment of manually labeled tract models for the uncinate fasciculus, the inferior longitudinal fasciculus and the corticospinal tract. In addition, we compare linear alignment using FLIRT based on either fractional anisotropy or anatomical volumes across-subjects, and find a comparable effect. Together these results imply a clear advantage to aligning anatomy as opposed to lower resolution DWI data even when the final goal is diffusion analysis.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Anisotropy
  • Aurovertins
  • Brain / anatomy & histology*
  • Diffusion
  • Diffusion Magnetic Resonance Imaging / methods*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Linear Models
  • Neural Pathways / anatomy & histology
  • Nonlinear Dynamics
  • Organ Size
  • Pyramidal Tracts / anatomy & histology
  • Reproducibility of Results


  • Aurovertins