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http://dx.doi.org/10.9717/kmms.2015.18.7.827

Compar ison of Level Set-based Active Contour Models on Subcor tical Image Segmentation  

Vongphachanh, Bouasone (Dept. of Computer Engineering, u-AHRC, Inje University)
Choi, Heung-Kook (Dept. of Computer Engineering, u-AHRC, Inje University)
Publication Information
Journal of Korea Multimedia Society / v.18, no.7, 2015 , pp. 827-833 More about this Journal
Abstract
In this paper, we have compared three level set-based active contour (LSAC) methods on inhomogeneous MR image segmentation which is known as an important role of brain diseases to diagnosis and treatment in early. MR image is often occurred a problem with similar intensities and weak boundaries which have been causing many segmentation methods. However, LSAC method could be able to segment the targets such as the level set based on the local image fitting energy, the local binary fitting energy, and local Gaussian distribution fitting energy. Our implemented and tested the subcortical image segmentations were the corpus callosum and hippocampus and finally demonstrated their effectiveness. Consequently, the level set based on local Gaussian distribution fitting energy has obtained the best model to accurate and robust for the subcortical image segmentation.
Keywords
Level Set-based Active Contour Method; Image Segmentation; Corpus Callosum; Hippocampus; Inhomogeneous Intensity;
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Times Cited By KSCI : 2  (Citation Analysis)
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