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Med Image Anal. 2008 Aug;12(4):442-51. doi: 10.1016/j.media.2008.01.003. Epub 2008 Feb 6.

Automatic segmentation of human brain sulci.

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1
Signal and Image Processing Laboratory, Department of Biomedical Engineering, University of California, Irvine, CA 92697-2755, USA. faguoy@uci.edu

Abstract

The neocortical surface has a rich and complex structure comprised of folds (gyri) and fissures (sulci). Sulci are important macroscopic landmarks for orientation on the cortex. A precise segmentation and labeling of sulci is helpful in human brain mapping studies relating brain anatomy and function. Due to their structural complexity and inter-subject variability, this is considered as a non-trivial task. An automatic algorithm is proposed to accurately segment neocortical sulci: vertices of a white/gray matter interface mesh are classified under a Bayesian framework as belonging to gyral and sulcal compartments using information about their geodesic depth and local curvature. Then, vertices are collected into sulcal regions by a watershed-like growing method. Experimental results demonstrate that the method is accurate and robust.

PMID:
18325826
DOI:
10.1016/j.media.2008.01.003
[Indexed for MEDLINE]
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