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用于大规模表面建模与配准的傅里叶方法。

Fourier method for large scale surface modeling and registration.

作者信息

Shen Li, Kim Sungeun, Saykin Andrew J

机构信息

Center for Neuroimaging, Division of Imaging Sciences, Department of Radiology, Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, 950 W Walnut St, R2 E124, Indianapolis, IN 46074.

出版信息

Comput Graph. 2009 Jun 1;33(3):299-311. doi: 10.1016/j.cag.2009.03.002.

Abstract

Spherical harmonic (SPHARM) description is a powerful Fourier shape modeling method for processing arbitrarily shaped but simply connected 3D objects. As a highly promising method, SPHARM has been widely used in several domains including medical imaging. However, its primary use has been focused on modeling small or moderately-sized surfaces that are relatively smooth, due to challenges related to its applicability, robustness and scalability. This paper presents an enhanced SPHARM framework that addresses these issues and show that the use of SPHARM can expand into broader areas. In particular, we present a simple and efficient Fourier expansion method on the sphere that enables large scale modeling, and propose a new SPHARM registration method that aims to preserve the important homological properties between 3D models. Although SPHARM is a global descriptor, our experimental results show that the proposed SPHARM framework can accurately describe complicated graphics models and highly convoluted 3D surfaces and the proposed registration method allows for effective alignment and registration of these 3D models for further processing or analysis. These methods greatly enable the potential of applying SPHARM to broader areas such as computer graphics, medical imaging, CAD/CAM, bioinformatics, and other related geometric modeling and processing fields.

摘要

球谐(SPHARM)描述是一种强大的傅里叶形状建模方法,用于处理任意形状但简单连通的三维物体。作为一种极具前景的方法,SPHARM已在包括医学成像在内的多个领域广泛应用。然而,由于其适用性、鲁棒性和可扩展性方面的挑战,其主要应用集中在对相对光滑的小尺寸或中等尺寸表面进行建模。本文提出了一个增强的SPHARM框架来解决这些问题,并表明SPHARM的应用可以扩展到更广泛的领域。特别是,我们提出了一种在球面上简单高效的傅里叶展开方法,以实现大规模建模,并提出了一种新的SPHARM配准方法,旨在保留三维模型之间重要的同调性质。尽管SPHARM是一种全局描述符,但我们的实验结果表明,所提出的SPHARM框架能够准确描述复杂的图形模型和高度复杂的三维表面,并且所提出的配准方法能够对这些三维模型进行有效对齐和配准,以便进一步处理或分析。这些方法极大地拓展了将SPHARM应用于计算机图形学、医学成像、CAD/CAM、生物信息学以及其他相关几何建模和处理领域等更广泛领域的潜力。

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