EXPERIMENTAL VALIDATION OF A NOVEL RECONSTRUCTION ALGORITHM FOR ELECTRICAL-IMPEDANCE TOMOGRAPHY BASED ON BACKPROJECTION OF LAGRANGE MULTIPLIERS

A novel approach to image reconstruction for electrical impedance tomo graphy (EIT) has been developed. It is based on a constrained optimiza tion technique for the reconstruction of difference resistivity images without finite-element modelling. It solves the inverse problem by op timizing a cost function under constraints, in the form of normalized boundary potentials. Its application to the neighbouring data collecti on method is presented here. Mathematical models are developed accordi ng to specified criteria. These express the reconstructed image in ter ms of one-dimensional Lagrange multiplier functions. The reconstructio n problem becomes one of estimating these functions from normalized bo undary potentials. This model is based on a cost criterion of the mini mization of the variance between the reconstructed and the true resist ivity distributions. The algorithm was tested on data collected in a c ylindrical saline-filled tank. A polyacrylamide rod was placed in vari ous positions with or without a peripheral plaster of Paris ring in pl ace. This was intended to resemble the conditions during Err of epilep tic seizures recorded with scalp or cortical electrodes in the human h ead. One advantage of this approach is that compensation for non-unifo rm initial conditions may be made, as this is a significant problem in imaging cerebral activity through the skull.