Genus zero surface conformal mapping and its application to brain surface mapping

By Xianfeng David Gu, Yalin Wang, Tony F. Chan, Paul M. Thompson, Shing-Tung Yau. IEEE Transactions on Medical Imaging, 2004

690 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design

View Paper: https://www.semanticscholar.org/paper/c9a44e7a3e79b6d97e6e054a235dc3ffcb5b4206

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Karthik Ramani
2. Ayan Sinha
3. Min Liu
4. Chiho Choi
5. Fupin Yao
6. Jing Bai
7. Nasser Kehtarnavaz
8. Shing-Tung Yau

In Computer Graphics and Computer-Aided Design

1. Karthik Ramani
2. Ayan Sinha
3. Jing Bai
4. Min Liu
5. Chiho Choi
6. Fupin Yao
7. Matthew F. Glasser
8. Shing-Tung Yau

Citations in the corpus

• Global conformal surface parameterization (2003, background): “…conformal parametrization , which preserves conformality Global conformal parameterization for closed genus zero surface has been addressed in 14 ; 11 ; 3 ; 12 Global conformal parameterization for closed surfaces with arbitrary genus is investigated in Gu and Yau’s work 12 ; 10 Global conformal…”
• Numerical Computation of Surface Conformal Mappings (2012, background): “Algorithmic details for discrete spherical harmonic maps can be found in [31].”
• Polynomial splines over hierarchical T-meshes (2008, background): “The reader is referred to [10,12,19] for some references on this topic.”
• Deep Learning 3D Shapes Using Alt-az Anisotropic 2-Sphere Convolution (2018, methodology): “Spherical parameterization methods (Peng & Timalsena (2016); Praun & Hoppe (2003); Gu et al. (2004)) map a genus-0 3D shape onto a sphere bijectively which provides a global framework for the spherical convolution.”
• Shape Registration with Spherical Cross Correlation (2008, background): “Our spherical parameterization was the global conformal map of Gu. et al. [12].”
• Brain Functional Localization: A Survey of Image Registration Techniques (2007, methodology): “On the basis of differential geometry, a conformal mapping approach to brain surface mapping has also been presented in [316].”
• Multimodal Surface Matching with Higher-Order Smoothness Constraints☆ (2017, methodology): “…surface registration methods have been proposed, which constrain alignment to the 2D cortical sheet (Durrleman et al., 2009; Fischl et al., 1999b; Gu et al., 2004; Lombaert et al., 2013; Lyu et al., 2015; Robinson et al., 2014; Tsui et al., 2013; Wright et al., 2015; Yeo et al., 2010; Van Essen,…”
• Deep Learning 3D Shape Surfaces Using Geometry Images (2016, methodology): “: There are two strategies for spherical parametrization of a 3D shape: (a) Authalic or area conserving, (b) Conformal or angle conserving .”