Seminars/Colloquia/Invited Talks

Seminars

Yalin Wang

Brain Surface Parameterization using Riemann Surface Structure

PLACE:	Clark 314
EVENT:	CIS Seminar Series
DATE:	March 14, 2006
TIME:	1:00 - 2:00

Abstract

We develop general approaches that parameterize brain anatomical surfaces with Riemann surface structure. All metric orientable surfaces are Riemann surfaces and admit conformal structure. With harmonic energy minimization, holomorphic 1-form and the Ricci flow methods, we can parameterize brain surfaces with various canonical surfaces such as sphere, Euclidean plane and punched hole disks. The resulting surface subdivision and the parameterizations of the components are intrinsic and stable. Our parameterization scheme offers a way to explicitly match landmark curves in anatomical surfaces such as the cortex, providing a surface-based framework to compare anatomy statistically and to generate grids on surfaces for PDE-based signal processing. Various applications of our research will also be discussed.

Brief Biography

Dr. Yalin Wang is an assistant researcher in UCLA Mathematics Department and Neurology Department. He received his Bachelor's and Master's degrees from the Department of Computer Science at Tsinghua University, China in 1994 and 1997, respectively. He received his Ph.D. degree from the Department of Electrical Engineering at University of Washington in 2002. His research interests include Computational Anatomy, Computer Vision and Computer Graphics. He won the best student paper award in "Fifth IAPR International workshop on Document Analysis System", Princeton, NJ, USA, August 2002.