Skip to Main content Skip to Navigation
Book sections

Brain Mapping using Topology Graphs Obtained by Surface Segmentation

Fabien Vivodtzev 1 Lars Linsen 2 Bernd Hamann 2 Kenneth I. Joy 2 Bruno A. Olshausen 3 
1 EVASION - Virtual environments for animation and image synthesis of natural objects
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : Brain mapping is a technique used to alleviate the tedious and time-consuming process of annotating brains by mapping existing annotations from brain atlases to individual brains. We introduce an automated surface-based brain mapping approach. After reconstructing a volume data set (trivariate scalar field) from raw imaging data, an isosurface is extracted approximating the brain cortex. The cortical surface can be segmented into gyral and sulcal regions by exploiting geometrical properties. Our surface segmentation is executed art a coarse level of resolution, such that discrete curvature estimates can be used to detect cortical regions. The topological information obtained from the surface segmentation is stored in a topology graph. A topology graph contains a high-level representation of the geometrical regions of a brain cortex. By deriving topology graphs for both atlas brain and individual brains, a graph node matching defines a mapping of brain cortex regions and their annotations.
Document type :
Book sections
Complete list of metadata
Contributor : Antoine Bégault Connect in order to contact the contributor
Submitted on : Friday, May 20, 2011 - 5:13:53 PM
Last modification on : Friday, February 4, 2022 - 3:24:12 AM
Long-term archiving on: : Friday, November 9, 2012 - 11:46:08 AM


Files produced by the author(s)


  • HAL Id : inria-00402130, version 1



Fabien Vivodtzev, Lars Linsen, Bernd Hamann, Kenneth I. Joy, Bruno A. Olshausen. Brain Mapping using Topology Graphs Obtained by Surface Segmentation. Bonneau, G.-P. and Ertl, T. and Nielson, G. .M. Scientific Visualization: The Visual Extraction of Knowledge from data, Springer, p. 35-48, 2005. ⟨inria-00402130⟩



Record views


Files downloads