Simulation of error propagation in finite element image reconstruction forelectrical impedance tomography

Using extensimulations, we have investigated the behaviour of finite elemen t image reconstruction for electrical impedance tomography in the presence of inaccuracies likely to exist in real measurements. This study characteri zes reconstruction when subjected to noise propagation using different exci tation patterns and modes of operation. Specifically, a generalized framewo rk for finite element image reconstruction is presented which allows electr ical impedance images to be recovered from data collected in either voltage , current or impedance modes of operation that correspond naturally to the allowable boundary condition types which determine unique model solutions t o the underlying partial differential equation as the basis for property es timation. Driving conditions consisting of electrode pairs, trigonometric o r synthesized trigonometric patterns have been considered. The simulations presented here are based on an arbitrary impedance distribution for which a pplied and observed voltages and currents were computed. The applied and ob served patterns were then processed identically to real data with the addit ion of 0, 0.1% and 1% random Gaussian noise. The mean squared error (MSE) b etween the reconstructed and exact impedance images constituted the measure of algorithmic performance. Our findings suggest that finite element recon struction tolerates noise on the measurement data better than on the applie d portion of the signal; pair excitations consistently produced the lowest MSE: noise appears to compound itself in the synthesized trigonometric patt erns mode, and the applied voltage mode consistently yields more accurate i mages in the presence of noise than the equivalent cases corresponding to c urrent mode. While only evaluated with trigonometric patterns. the impedanc e mode generally produced the lowest MSE in a limited set of simulation com parisons.