A geometric method for automatic extraction of sulcal fundi

Chiu Yen Kao, Michael Hofer, Guillermo Sapiro, Josh Stern, Kelly Rehm, David A. Rottenberg

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Sulcal fundi are 3-D curves that lie in the depths of the cerebral cortex and, in addition to their intrinsic value in brain research, are often used as landmarks for downstream computations in brain imaging. In this paper, we present a geometric algorithm that automatically extracts the sulcal fundi from magnetic resonance images and represents them as spline curves lying on the extracted triangular mesh representing the cortical surface. The input to our algorithm is a triangular mesh representation of an extracted cortical surface as computed by one of several available software packages for performing automated and semi-automated cortical surface extraction. Given this input we first compute a geometric depth measure for each triangle on the cortical surface mesh, and based on this information we extract sulcal regions by checking for connected regions exceeding a depth threshold. We then identify endpoints of each region and delineate the fundus by thinning the connected region while keeping the endpoints fixed. The curves, thus, defined are regularized using weighted splines on the surface mesh to yield high-quality representations of the sulcal fundi. We present the geometric framework and validate it with real data from human brains. Comparisons with expert-labeled sulcal fundi are part of this validation process.

Original languageEnglish (US)
Pages (from-to)530-540
Number of pages11
JournalIEEE Transactions on Medical Imaging
Volume26
Issue number4
DOIs
StatePublished - Apr 1 2007

Bibliographical note

Funding Information:
Manuscript received August 28, 2006; revised September 15, 2006. This work was supported in part by the National Institutes of Health (NIH) through the Human Brain Project P20 under Grant EB02013, in part by the Austrian Science Fund under Grant S92 and and Grant P18865, in part by the NSF, in part by the ONR, in part by the NGA, in part by the DARPA, and in part by the NIH-Novel PDEs for Cortical Mapping and Analysis in Disease. Asterisk indicates corresponding author.

Keywords

  • Brain imaging
  • Brain warping
  • MRI
  • Sulcal fundi
  • Surface splines
  • Thinning

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