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Compar ison of Level Set-based Active Contour Models on Subcor tical Image Segmentation
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 Title & Authors
Compar ison of Level Set-based Active Contour Models on Subcor tical Image Segmentation
Vongphachanh, Bouasone; Choi, Heung-Kook;
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 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;
 Language
English
 Cited by
1.
Contrast-enhanced Bias-corrected Distance-regularized Level Set Method Applied to Hippocampus Segmentation,;;;;;;

한국멀티미디어학회논문지, 2016. vol.19. 8, pp.1236-1247 crossref(new window)
1.
Contrast-enhanced Bias-corrected Distance-regularized Level Set Method Applied to Hippocampus Segmentation, Journal of Korea Multimedia Society, 2016, 19, 8, 1236  crossref(new windwow)
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