基于全脑结构连通性和连续连通性分析来注册皮质表面。
Registering cortical surfaces based on whole-brain structural connectivity and continuous connectivity analysis.
作者信息
Gutman Boris, Leonardo Cassandra, Jahanshad Neda, Hibar Derrek, Eschenburg Kristian, Nir Talia, Villalon Julio, Thompson Paul
出版信息
Med Image Comput Comput Assist Interv. 2014;17(Pt 3):161-8. doi: 10.1007/978-3-319-10443-0_21.
Abstract
We present a framework for registering cortical surfaces based on tractography-informed structural connectivity. We define connectivity as a continuous kernel on the product space of the cortex, and develop a method for estimating this kernel from tractography fiber models. Next, we formulate the kernel registration problem, and present a means to non-linearly register two brains' continuous connectivity profiles. We apply theoretical results from operator theory to develop an algorithm for decomposing the connectome into its shared and individual components. Lastly, we extend two discrete connectivity measures to the continuous case, and apply our framework to 98 Alzheimer's patients and controls. Our measures show significant differences between the two groups.
摘要
我们提出了一个基于纤维束成像引导的结构连通性来配准皮质表面的框架。我们将连通性定义为皮质乘积空间上的连续核，并开发了一种从纤维束成像纤维模型估计该核的方法。接下来，我们阐述核配准问题，并提出一种对两个大脑的连续连通性轮廓进行非线性配准的方法。我们应用算子理论的理论结果来开发一种将连接组分解为其共享和个体成分的算法。最后，我们将两种离散连通性度量扩展到连续情况，并将我们的框架应用于98名阿尔茨海默病患者和对照组。我们的度量显示两组之间存在显著差异。
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