title: Electrical impedance tomography problem with inaccurately known boundary and contact impedances.
abstract: In electrical impedance tomography (EIT) electric currents are injected into a body with unknown electromagnetic properties through a set of contact electrodes at the boundary of the body. The resulting voltages are measured on the same electrodes and the objective is to reconstruct the unknown conductivity function inside the body based on these data. All the traditional approaches to the reconstruction problem assume that the boundary of the body and the electrode-skin contact impedances are known a priori. However, in clinical experiments one usually lacks the exact knowledge of the boundary and contact impedances, and therefore, approximate model domain and contact impedances have to be used in the image reconstruction. However, it has been noticed that even small errors in the shape of the computation domain or contact impedances can cause large systematic artefacts in the reconstructed images, leading to loss of diagnostically relevant information. In a recent paper (Kolehmainen , 2006), we showed how in the 2-D case the errors induced by the inaccurately known boundary can be eliminated as part of the image reconstruction and introduced a novel method for finding a deformed image of the original isotropic conductivity using the theory of TeichmUller mappings. In this paper, the theory and reconstruction method are extended to include the estimation of unknown contact impedances. The method is implemented numerically and tested with experimental EIT data. The results show that the systematic errors caused by inaccurately known boundary and contact impedances can efficiently be eliminated by the reconstruction method.
authors.affiliation: Department of Applied Physics, University of Kuopio, FIN-70211 Kuopio, Finland.
authors.forename: Ville
authors.initials: V
authors.lastname: Kolehmainen
authors.forename: Matti
authors.initials: M
authors.lastname: Lassas
authors.forename: Petri
authors.initials: P
authors.lastname: Ola
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D017097:Electric Impedance; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D019047:Phantoms, Imaging; D010992:Plethysmography, Impedance / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014054:Tomography / Q000379:methods