Approximation error method for imaging the human head by electrical impedance tomography

This work considers electrical impedance tomography imaging of the human , with the ultimate goal of locating and classifying a stroke in emergency . One of the main difficulties in the envisioned application is that the locations and the shape of the head are not precisely known, leading significant imaging artifacts due to impedance tomography being sensitive to errors. In this study, the natural variations in the geometry of the and skull are modeled based on a library of head anatomies. The effect of variations, as well as that of misplaced electrodes, on (absolute) tomography measurements is in turn modeled by the approximation error . This enables reliably reconstructing the conductivity perturbation by the stroke in an average head model, instead of the actual head, to its average conductivity levels. The functionality of a certain -preferring reconstruction algorithm for locating the stroke is via numerical experiments based on simulated three-dimensional .