Electrical Impedance Tomography (EIT) image reconstruction for the human forearm

Abstract

This thesis addresses the principles and algorithms of image reconstruction used in electrical impedance tomography (EIT). It is a low cost, portable and non-invasive medical imaging technique. In this development EIT is used for the nerve location in the human forearm. The work addresses the current injection and voltage acquisition methods, geometry definitions and the finite element method for meshing and impedance map reconstruction. In order to analyze different features, a software tool kit called EIDORS was used for the target application of EIT applied for human forearm tomography. This thesis most important contribution is the development of an EIT methodology for image reconstruction from the impedance map of a human forearm using EIDORS. Different image reconstruction algorithms and prior information methods are evaluated and analyzed to solve the EIT inverse problem for the human forearm. It was found that although the methodology could be successfully implemented, the desired resolution for the precise identification of nerves was not sufficient for practical configurations.