Lui Lok Ming, Wang Yalin, Chan Tony F, Thompson Paul M
Department of Mathematics, UCLA, USA.
Med Image Comput Comput Assist Interv. 2006;9(Pt 2):308-15. doi: 10.1007/11866763_38.
In this paper, we present algorithms to automatically detect and match landmark curves on cortical surfaces to get an optimized brain conformal parametrization. First, we propose an automatic landmark curve tracing method based on the principal directions of the local Weingarten matrix. Our algorithm obtains a hypothesized landmark curves using the Chan-Vese segmentation method, which solves a Partial Differential Equation (PDE) on a manifold with global conformal parameterization. Based on the global conformal parametrization of a cortical surface, our method adjusts the landmark curves iteratively on the spherical or rectangular parameter domain of the cortical surface along its principal direction field, using umbilic points of the surface as anchors. The landmark curves can then be mapped back onto the cortical surface. Experimental results show that the landmark curves detected by our algorithm closely resemble these manually labeled curves. Next, we applied these automatically labeled landmark curves to generate an optimized conformal parametrization of the cortical surface, in the sense that homologous features across subjects are caused to lie at the same parameter locations in a conformal grid. Experimental results show that our method can effectively help in automatically matching cortical surfaces across subjects.
在本文中，我们提出了一些算法，用于自动检测和匹配皮质表面上的地标曲线，以获得优化的大脑共形参数化。首先，我们提出了一种基于局部魏因加滕矩阵主方向的自动地标曲线追踪方法。我们的算法使用Chan-Vese分割方法获得一个假设的地标曲线，该方法在具有全局共形参数化的流形上求解一个偏微分方程（PDE）。基于皮质表面的全局共形参数化，我们的方法在皮质表面的球形或矩形参数域上沿着其主方向场，以表面的脐点为锚点，迭代地调整地标曲线。然后可以将地标曲线映射回皮质表面。实验结果表明，我们算法检测到的地标曲线与这些手动标记的曲线非常相似。接下来，我们应用这些自动标记的地标曲线来生成皮质表面的优化共形参数化，即跨受试者的同源特征在共形网格中的相同参数位置处。实验结果表明，我们的方法可以有效地帮助自动匹配跨受试者的皮质表面。
