Multi-scale characterization of white matter tract geometry

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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.

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Savadjiev, P., Rathi, Y., Bouix, S., Verma, R., & Westin, C. F. (2012). Multi-scale characterization of white matter tract geometry. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7512 LNCS, pp. 34–41). Springer Verlag. https://doi.org/10.1007/978-3-642-33454-2_5

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