Abstract
In this work we demonstrate how Finsler geometry—and specifically the related geodesic tractography— can be levied to analyze structural connections between different brain regions. We present new theoretical developments which support the definition of a novel Finsler metric and associated con-nectivity measures, based on closely related works on the Riemannian framework for diffusion MRI. Using data from the Human Connectome Project, as well as population data from an autism spectrum disorder study, we demonstrate that this new Finsler metric, together with the new connectivity measures, results in connectivity maps that are much closer to known tract anatomy compared to previous geodesic connectivity methods. Our implementation can be used to compute geodesic distance and connectivity maps for segmented areas, and is publicly available.
Footnotes
↵† Joint first authors.
Funding: This work was supported by NIH grants P41EB015902, R01MH074794, and R01MH092862, and by a NARSAD Young Investigator award (grant number 22591) by the Brain and Behavior Research Foundation to Peter Savadjiev. The authors also gratefully acknowledge NWO (No. 617.001.202) and the Villum Foundation for financial support. The work of Andrea Fuster is part of the research programme of the Foundation for Fundamental Research on Matter (FOM), which is financially supported by the Netherlands Organisation for Scientific Research (NWO). Results presented in this work have been published as part of the main author’s PhD thesis “Finsler Geometry and Diffusion MRI” (Eindhoven University of Technology, ISBN: 978-90-386-4274-1).