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http://dx.doi.org/10.9717/kmms.2013.16.9.1018

Comparison of Active Contour and Active Shape Approaches for Corpus Callosum Segmentation  

Adiya, Enkhbolor (Dept of Computer Engineering, Inje University)
Izmantoko, Yonny S. (Dept of Computer Engineering, Inje University)
Choi, Heung-Kook (Dept of Computer Engineering, UHRC, Inje University)
Publication Information
Journal of Korea Multimedia Society / v.16, no.9, 2013 , pp. 1018-1030 More about this Journal
Abstract
The corpus callosum is the largest connective structure in the brain, and its shape and size are correlated to sex, age, brain growth and degeneration, handedness, musical ability, and neurological diseases. Manually segmenting the corpus callosum from brain magnetic resonance (MR) image is time consuming, error prone, and operator dependent. In this paper, two semi-automatic segmentation methods are present: the active contour model-based approach and the active shape model-based approach. We tested these methods on an MR image of the human brain and found that the active contour approach had better segmentation accuracy but was slower than the active shape approach.
Keywords
Corpus callosum; distribution; segmentation; active contour; active shape;
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