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基于拉普拉斯-贝尔特拉米特征映射的调和曲面映射

Harmonic surface mapping with Laplace-Beltrami eigenmaps.

作者信息

Shi Yonggang, Lai Rongjie, Kern Kyle, Sicotte Nancy, Dinov Ivo, Toga Arthur W

机构信息

Lab of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA.

出版信息

Med Image Comput Comput Assist Interv. 2008;11(Pt 2):147-54. doi: 10.1007/978-3-540-85990-1_18.

Abstract

In this paper we propose a novel approach for the mapping of 3D surfaces. With the Reeb graph of Laplace-Beltrami eigenmaps, our method automatically detects stable landmark features intrinsic to the surface geometry and use them as boundary conditions to compute harmonic maps to the unit sphere. The resulting maps are diffeomorphic, robust to natural pose variations, and establish correspondences for geometric features shared across population. In the experiments, we demonstrate our method on three subcortical structures: the hippocampus, putamen, and caudate nucleus. A group study is also performed to generate a statistically significant map of local volume losses in the hippocampus of patients with secondary progressive multiple sclerosis.

摘要

在本文中,我们提出了一种用于三维表面映射的新方法。借助拉普拉斯 - 贝尔特拉米特征映射的里布图,我们的方法能自动检测表面几何结构固有的稳定地标特征,并将其用作边界条件来计算到单位球面的调和映射。所得映射是微分同胚的,对自然姿态变化具有鲁棒性,并为群体中共享的几何特征建立对应关系。在实验中,我们在三种皮质下结构上展示了我们的方法:海马体、壳核和尾状核。我们还进行了一项群体研究,以生成继发性进行性多发性硬化症患者海马体局部体积损失的具有统计学意义的图谱。

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