EXTRACTING GEOMETRICAL FEATURES & PEAK FRACTIONAL ANISOTROPY FROM THE ODF FOR WHITE MATTER CHARACTERIZATION - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2011

EXTRACTING GEOMETRICAL FEATURES & PEAK FRACTIONAL ANISOTROPY FROM THE ODF FOR WHITE MATTER CHARACTERIZATION

Abstract

Spherical Functions (SF) play a pivotal role in Diffusion MRI (dMRI) in representing sub-voxel-resolution micro- architectural information of the underlying tissue. This in- formation is encoded in the geometric shape of the SF. In this paper we use a polynomial approach to extract geometric characteristics from SFs in dMRI such as the maxima, min- ima and saddle-points. We then use differential geometric tools to quantify further details such as principal curvatures at the extrema. Finally we propose new scalar measures like the Peak Fractional Anisotropy (PFA) and Total-PFA, to represent this rich source of information for characteriz- ing white-matter (WM) fibers. As an example we illustrate our method on the Orientation Distribution Function (ODF) estimated from real data.
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Dates and versions

hal-00645804 , version 1 (28-11-2011)

Identifiers

  • HAL Id : hal-00645804 , version 1

Cite

Aurobrata Ghosh, Rachid Deriche. EXTRACTING GEOMETRICAL FEATURES & PEAK FRACTIONAL ANISOTROPY FROM THE ODF FOR WHITE MATTER CHARACTERIZATION. IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Wright, Steve and Pan, Xiaochuan and Liebling, Michael, Mar 2011, Chicago, United States. ⟨hal-00645804⟩
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