Oliver Ernst with Erkki Somersalo
Optimal Current Patterns and Resolution Limitations of the Bayesian Methodology in EIT
One of the applications of the Bayesian methodology is to the determination of the electrical admittivity distribution from measurement data in Electrical Impedance Tomography (EIT). Since this inverse problem is ill-posed, a spectrum of algorithms have been proposed as solutions. However, one of the principal challenges remains the low resolution as a result of the reconstruction. This project will focus on determining the optimal current patterns for electrodes that lead to maximum distinguishability of regions of electrical conductivity. Furthermore, the sensitivity of the reconstructed regions to variations in the measurement data will be quantitatively assessed. Numerical simulations of artificial conductivity distributions combined with electrode models will be used to generate synthetic data to be tested.