Automated segmentation of the corpus callosum in midsagittal brain magnetic resonance images
Automated segmentation of the corpus callosum in midsagittal brain magnetic resonance images
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DOI：
10.1117/1.602449
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发表时间：
2000-04-01
影响因子：
1.3
通讯作者：
Unser, M
中科院分区：
文献类型：
--
作者：
Lee, C;Huh, S;Unser, M
我们提出了一种新的算法，找到胼胝体自动从正中矢状面的大脑MR（磁共振）图像使用的统计特性和形状信息的胼胝体。我们首先提取区域满足胼胝体的统计特性（灰度分布），具有相对较高的强度值。然后，我们试图找到一个区域匹配的形状信息的胼胝体。为了匹配形状信息，我们提出了一种新的有向窗口区域生长算法，而不是使用传统的轮廓匹配。该算法的一个创新特点是，我们自适应地放宽统计要求，直到我们找到一个区域匹配的形状信息。在初始分割后，提出了一种有向边界路径修剪算法，以去除一些不希望的伪影，特别是在胼胝体的顶部。该算法被应用于120多幅图像，并提供了有前途的结果。(C)2000年，美国光电仪器工程师学会。[S0091-3286（00）00604-8]。
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. (C) 2000 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(00)00604-8].