Date : July 10, 2019, 10:30 a.m. - Room :Salle du conseil

Regularization Approaches for Ill-Posed Inverse Problems in Electrical Impedance and Diffuse Optical Tomography

Taufiquar Kahn, professeur - Clemson University (USA)

In this talk, we provide an introduction to regularization approaches for solving ill-posed inverse problems such as Electrical Impedance Tomography (EIT) and Diffuse Optical Tomography (DOT). There is also tremendous growth in devising new techniques from regularization theory both deterministic and statistical such as sparsity regularization, Bayesian inversion using Markov Chain Monte Carlo (MCMC) methods etc.  We discuss several deterministic and statistical approaches for image reconstruction in EIT and DOT. The complete electrode model for the inverse problem in EIT for damage detection in concrete will also be presented. The appropriate function spaces and regularization required to solve this ill-posed inverse problem is also described. Both the deterministic and the statistical inversion approaches are compared with preliminary results using data.