Adaptive Mesh Refinement for Electrical Impedance Tomography

Adaptive mesh refinement (AMR) techniques can be applied to increase the efficiency of Electrical Impedance Tomography (EIT) reconstruction algorithms by reducing computational and storage cost as well as providing problem-dependent solution structures. A self-adaptive refinement algorithm based on an a posteriori error estimate has been developed and its results are shown in comparison to uniform mesh refinement for a simple head model. Keywords: nonlinear electrical impedance tomography, adaptive mesh refinement, h-refinement, p-refinement, efficiency, improved convergence