Skip to Main content Skip to Navigation
Conference papers

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

Aurobrata Ghosh 1 Rachid Deriche 1
1 ATHENA - Computational Imaging of the Central Nervous System
CRISAM - Inria Sophia Antipolis - Méditerranée
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.
Document type :
Conference papers
Complete list of metadatas

Cited literature [17 references]  Display  Hide  Download

https://hal.inria.fr/hal-00645804
Contributor : Aurobrata Ghosh <>
Submitted on : Monday, November 28, 2011 - 4:26:32 PM
Last modification on : Thursday, March 5, 2020 - 5:34:48 PM
Long-term archiving on: : Wednesday, February 29, 2012 - 2:30:06 AM

File

output.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-00645804, version 1

Collections

Citation

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⟩

Share

Metrics

Record views

1352

Files downloads

193