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首页> 外文期刊>Computational and mathematical methods in medicine >Automatic Extraction of the Centerline of Corpus Callosum from Segmented Mid-Sagittal MR Images
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Automatic Extraction of the Centerline of Corpus Callosum from Segmented Mid-Sagittal MR Images

机译：从矢状中段MR图像中自动提取Call体中心线

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The centerline, as a simple and compact representation of object shape, has been used to analyze variations of the human callosal shape. However, automatic extraction of the callosal centerline remains a sophisticated problem. In this paper, we propose a method of automatic extraction of the callosal centerline from segmented mid-sagittal magnetic resonance (MR) images. A model-based point matching method is introduced to localize the anterior and posterior endpoints of the centerline. The model of the endpoint is constructed with a statistical descriptor of the shape context. Active contour modeling is adopted to drive the curve with the fixed endpoints to approximate the centerline using the gradient of the distance map of the segmented corpus callosum. Experiments with 80 segmented mid-sagittal MR images were performed. The proposed method is compared with a skeletonization method and an interactive method in terms of recovery error and reproducibility. Results indicate that the proposed method outperforms skeletonization and is comparable with and sometimes better than the interactive method.
机译：中心线作为对象形状的简单而紧凑的表示形式，已被用于分析人类call体形状的变化。然而，call骨中心线的自动提取仍然是一个复杂的问题。在本文中，我们提出了一种从分段中矢状核磁共振（MR）图像中自动提取call骨中心线的方法。引入了基于模型的点匹配方法来定位中心线的前后端点。使用形状上下文的统计描述符构造端点模型。采用主动轮廓建模，使用分段的s体距离图的梯度，以固定的端点驱动曲线逼近中心线。进行了80幅中矢状MR分割图像的实验。在恢复误差和可再现性方面，将所提出的方法与骨架化方法和交互式方法进行了比较。结果表明，所提出的方法优于骨架化方法，可与交互式方法媲美，有时甚至优于交互式方法。

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