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Effective Brain Contour Segmentation based on Active Contour Model

Authors
은성종정은영박동균
Issue Date
2017
Publisher
차세대컨버전스정보서비스학회
Keywords
R2-map; Brain Segmentation; MR theory; Active Contour Model; Curve Fitting
Citation
차세대컨버전스정보서비스기술논문지, v.6, no.2, pp.75 - 88
Journal Title
차세대컨버전스정보서비스기술논문지
Volume
6
Number
2
Start Page
75
End Page
88
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/7342
ISSN
2384-101X
Abstract
Object recognition is usually processed based on region segmentation algorithm. This paper suggests effective region segmentation method based on R2-map within the magnetic resonance (MR) theory. When we do pre-processing, proposed method was composed of R2-map process. And then we do the Gray-white matter segmentation by Active Contour Model(ACM) in post-processing. In this study, the experiment had been conducted using images including the brain region and by getting up contrast enhancement image of R2-map for segmentation to extract region (white matter) segmentation even when the border line was not clear. As a result, an average area difference of 5.8%, which was higher than the accuracy of conventional region segmentation algorithm, was obtained.
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