A geometric method for automatic extraction of sulcal fundi
A geometric method for automatic extraction of sulcal fundi
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DOI：
10.1109/tmi.2006.886810
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发表时间：
2007-04-01
影响因子：
10.6
通讯作者：
Rottenberg, David A.
中科院分区：
文献类型：
--
作者：
Kao, Chiu-Yen;Hofer, Michael;Rottenberg, David A.
脑沟底是位于大脑皮层深处的三维曲线，除了在大脑研究中的内在价值外，还经常用作大脑成像下游计算的地标。在本文中，我们提出了一种几何算法，自动提取脑沟底磁共振图像，并表示它们作为样条曲线躺在提取的三角形网格表示皮质表面。我们的算法的输入是一个三角形网格表示提取的皮质表面计算的几个可用的软件包进行自动和半自动皮质表面提取。给定此输入，我们首先计算皮质表面网格上每个三角形的几何深度测量，并基于此信息，我们通过检查超过深度阈值的连接区域来提取脑沟区域。然后，我们确定每个区域的端点，并通过在保持端点固定的同时细化连接区域来描绘眼底。因此，定义的曲线使用表面网格上的加权样条进行正则化，以产生沟底的高质量表示。我们提出的几何框架，并验证它与人类大脑的真实的数据。与专家标记的沟底比较是验证过程的一部分。
Sulcal fundi are 3-D curves that lie in the depths of the cerebral cortex and, in addition to their intrinsic value in brain research, are often used as landmarks for downstream computations in brain imaging. In this paper, we present a geometric algorithm that automatically extracts the sulcal fundi from magnetic resonance images and represents them as spline curves lying on the extracted triangular mesh representing the cortical surface. The input to our algorithm is a triangular mesh representation of an extracted cortical surface as computed by one of several available software packages for performing automated and semi-automated cortical surface extraction. Given this input we first compute a geometric depth measure for each triangle on the cortical surface mesh, and based on this information we extract sulcal regions by checking for connected regions exceeding a depth threshold. We then identify endpoints of each region and delineate the fundus by thinning the connected region while keeping the endpoints fixed. The curves, thus, defined are regularized using weighted splines on the surface mesh to yield high-quality representations of the sulcal fundi. We present the geometric framework and validate it with real data from human brains. Comparisons with expert-labeled sulcal fundi are part of this validation process.