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Optical Engineering

Automated segmentation of the corpus callosum in midsagittal brain magnetic resonance images
Author(s): Chulhee Lee; Shin Huh; Terence A. Ketter; Michael A. Unser
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Paper Abstract

We propose a new algorithm to find the corpus callosum automatically from midsagittal brain MR (magnetic resonance) images using the statistical characteristics and shape information of the corpus callosum. We first extract regions satisfying the statistical characteristics (gray level distributions) of the corpus callosum that have relatively high intensity values. Then we try to find a region matching the shape information of the corpus callosum. In order to match the shape information, we propose a new directed window region growing algorithm instead of using conventional contour matching. An innovative feature of the algorithm is that we adaptively relax the statistical requirement until we find a region matching the shape information. After the initial segmentation, a directed border path pruning algorithm is proposed in order to remove some undesired artifacts, especially on the top of the corpus callosum. The proposed algorithm was applied to over 120 images and provided promising results.

Paper Details

Date Published: 1 April 2000
PDF: 12 pages
Opt. Eng. 39(4) doi: 10.1117/1.602449
Published in: Optical Engineering Volume 39, Issue 4
Show Author Affiliations
Chulhee Lee, Yonsei Univ. (South Korea)
Shin Huh, Yonsei Univ. (South Korea)
Terence A. Ketter, National Institutes of Health (United States)
Michael A. Unser, Swiss Federal Institute of Technology (Switzerland)


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