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