Cortical surface flattening using least square conformal mapping with minimal metric distortion

Lili Ju, Josh Stern, Kelly Rehm, Kirt Schaper, Monica Hurdal, David Rottenberg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Scopus citations

Abstract

Although flattening a cortical surface necessarily introduces metric distortion due to the non-constant Gaussian curvature of the surface, the Riemann Mapping Theorem states that continuously differentiable surfaces can be mapped without angular distortion. We apply the so-called least-square conformal mapping approach to flatten a patch of the cortical surface onto planar regions and to produce spherical conformal maps of the entire cortex while minimizing metric distortion within the class of conformal maps. Our method, which preserves angular information and controls metric distortion, only involves the solution of a linear system and a nonlinear minimization problem with three parameters and is a very fast approach.

Original languageEnglish (US)
Title of host publication2004 2nd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationMacro to Nano
Pages77-80
Number of pages4
StatePublished - Dec 1 2004
Event2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano - Arlington, VA, United States
Duration: Apr 15 2004Apr 18 2004

Publication series

Name2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Volume1

Other

Other2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
CountryUnited States
CityArlington, VA
Period4/15/044/18/04

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