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Voxel-Wise Clustering of Tractography Data for Building Atlases of Local Fiber Geometry

  • Irene BrusiniEmail author
  • Daniel Jörgens
  • Örjan Smedby
  • Rodrigo Moreno
Conference paper
Part of the Mathematics and Visualization book series (MATHVISUAL)

Abstract

This paper aims at proposing a method to generate atlases of white matter fibers’ geometry that consider local orientation and curvature of fibers extracted from tractography data. Tractography was performed on diffusion magnetic resonance images from a set of healthy subjects and each tract was characterized voxel-wise by its curvature and Frenet–Serret frame, based on which similar tracts could be clustered separately for each voxel and each subject. Finally, the centroids of the clusters identified in all subjects were clustered to create the final atlas. The proposed clustering technique showed promising results in identifying voxel-wise distributions of curvature and orientation. Two tractography algorithms (one deterministic and one probabilistic) were tested for the present work, obtaining two different atlases. A high agreement between the two atlases was found in several brain regions. This suggests that more advanced tractography methods might only be required for some specific regions in the brain. In addition, the probabilistic approach resulted in the identification of a higher number of fiber orientations in various white matter areas, suggesting it to be more adequate for investigating complex fiber configurations in the proposed framework as compared to deterministic tractography.

Keywords

Tractography Fiber clustering Brain atlases 

Notes

Acknowledgements

Data were partially provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Irene Brusini
    • 1
    • 2
    Email author
  • Daniel Jörgens
    • 1
  • Örjan Smedby
    • 1
  • Rodrigo Moreno
    • 1
  1. 1.Department of Biomedical Engineering and Health SystemsKTH Royal Institute of TechnologyStockholmSweden
  2. 2.Department of Neurobiology, Care Sciences and SocietyKarolinska InstitutetStockholmSweden

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