## Abstract

Electrical Impedance tomography (EIT) imaging suffers greatly from the illposedness of the corresponding inverse problem. This is mainly caused by the high degree of freedom and the relatively large noise. One attempt to circumvent these difficulties is to use dual models. This article introduces a clustering based non-uniform dual model construction. With this framework, finite elements are grouped to reduce the complexity in inverse computations. The simulation and experiment results indicated that the k-means clustering method did not only preserve the sharp variations over conductivity mediums but also greatly filtered out artefacts found in the standard approach.

## Comments (0)

General note:By using the comment function on degruyter.com you agree to our Privacy Statement. A respectful treatment of one another is important to us. Therefore we would like to draw your attention to our House Rules.