Finite element approximations for electrical impedance tomography

Venue: Room 200-9, Run Run Shaw Business Administration Building

Speaker: 

Dr. Bangti Jin received Ph.D. degree in applied mathematics from the Chinese University of Hong Kong in 2008. Previously, he was an assistant Professor of mathematics at University of California, Riverside (2013-2014), a visiting assistant professor at Texas A&M University (2010-2013), an Alexandre von Humboldt Postdoctoral Researcher at the University of Bremen (2009-2010). He is currently a Reader in inverse problems in the Department of Computer Science, University College London, London, U.K. His research interests include computational inverse problems and numerical analysis of differential equations.

Abstract:

Electrical impedance tomography is a noninvasive medical imaging modality, which aims at recovering the conductivity from the boundary electrode voltage measurements. Most reconstruction techniques employ Tikhonov regularization with different penalties, and then discretize the optimization by means of finite element methods. In this talk, I will describe finite element approximations on both uniform and adaptive meshes, and discuss their convergence properties. I will illustrate the discussions with numerical experiments.