Chung Moo K, Dalton Kim M, Davidson Richard J
Department of Biostatistics and Medical Informatics, and the Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, WI 53706, USA.
IEEE Trans Med Imaging. 2008 Aug;27(8):1143-51. doi: 10.1109/TMI.2008.918338.
We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric tensors, which are obtained from the smooth functional parametrization of a cortical mesh. For the smooth parametrization, we have developed a novel weighted spherical harmonic (SPHARM) representation, which generalizes the traditional SPHARM as a special case. For a specific choice of weights, the weighted-SPHARM is shown to be the least squares approximation to the solution of an isotropic heat diffusion on a unit sphere. The main aims of this paper are to present the weighted-SPHARM and to show how it can be used in the tensor-based morphometry. As an illustration, the methodology has been applied in the problem of detecting abnormal cortical regions in the group of high functioning autistic subjects.
我们提出了一种新的基于张量的形态计量框架，该框架使用局部面积元素来量化皮质形状变化。局部面积元素是根据黎曼度量张量计算得出的，这些张量是从皮质网格的平滑函数参数化中获得的。对于平滑参数化，我们开发了一种新颖的加权球谐（SPHARM）表示，它将传统的SPHARM作为特殊情况进行了推广。对于特定的权重选择，加权SPHARM被证明是单位球面上各向同性热扩散解的最小二乘近似。本文的主要目的是介绍加权SPHARM，并展示它如何用于基于张量的形态计量学。作为一个例证，该方法已应用于检测高功能自闭症受试者群体中异常皮质区域的问题。
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