An automated pipeline for cortical sulcal fundi extraction.

An automated pipeline for cortical sulcal fundi extraction.
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用于提取皮质沟底的自动化管道。

DOI:
10.1016/j.media.2010.01.005
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发表时间:
2010-06
影响因子:
10.9
通讯作者:
Liu, Tianming
Liu, Tianming
中科院分区:
工程技术1区
文献类型:
--
作者:
Li, Gang;Guo, Lei;Nie, Jingxin;Liu, Tianming

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在这篇文章中,我们提出了一种新的从三角化的皮质表面提取沟底的自动化管道。该方法由四个连续的步骤组成。首先,我们采用有限差分方法来估计每个顶点沿主方向的主曲率、主方向和曲率导数。然后,我们基于曲率和曲率导数来检测大脑皮质表面每个三角形中的脑沟底段。然后,我们将沟底段连接成连续的曲线。最后,在皮质表面采用快速行进的方法,将破裂的槽底与平滑的槽底进行连接。该方法无需人工干预,即可利用曲率和曲率导数求出精确的槽形函数。该方法被应用于10幅正常大脑皮质内表面的磁共振图像。我们由专家对人工标记的脑沟底提取方法的准确性进行了定量评估。在10幅主题图像上,自动提取的主要脑沟底与专家标记的结果之间的平均偏差在1.0 mm左右,表明了该方法的良好性能。
In this paper, we propose a novel automated pipeline for extraction of sulcal fundi from triangulated cortical surfaces. This method consists of four consecutive steps. Firstly, we adopt a finite difference method to estimate principal curvatures, principal directions and curvature derivatives, along the principal directions, for each vertex. Then, we detect the sulcal fundi segment in each triangle of the cortical surface based on curvatures and curvature derivatives. Afterwards, we link the sulcal fundi segments into continuous curves. Finally, we connect breaking sulcal fundi and smooth bumping sulcal fundi by using the fast marching method on the cortical surface. The proposed method can find the accurate sulcal fundi using curvatures and curvature derivatives without any manual interaction. The method was applied to ten normal brain MR images on inner cortical surfaces. We quantitatively evaluated the accuracy of the sulcal fundi extraction method using manually labeled sulcal fundi by experts. The average difference between automatically extracted major sulcal fundi and the expert labeled results is consistently around 1.0 mm on ten subject images, indicating the good performance of the proposed method.
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