Tackling modelling error in the application of electrical impedance tomography to the head

In the head application of Electrical Impedance Tomography (EIT), reconstruction of voltage measurements for a conductivity distribution image using an ordinary method, the absolute imaging approach, is impossible due to the traditional ignorance of modelling error. The modelling error comes from the inaccuracy of geometry and structure, which are unable to be known accurately in practice, and are usually large in head application of EIT. Difference imaging is an alternative approach which is able to reduce the size of this error, but it introduces other kinds of error. In this work, we demonstrate that in situations like head EIT, the nonlinear difference imaging approach can reconstruct difference conductivity effectively: the reduced modelling error and the new errors arising are able to be ignored, because they are much smaller than the original modelling error. The magnitude of conductivity change in the head-like situation is also investigated, and a selection scheme for the initial guess in the reconstruction process is also proposed.