Overview

This chapter describes electrical impedance imaging techniques providing information on electrical properties of biological tissues. Sections on Electrical Impedance Tomography (EIT) deal with cross-sectional image reconstructions of conductivity and/or permittivity distributions from boundary measurements of current-voltage data. After mathematically defining the imaging problem in EIT, image reconstruction algorithms are discussed. Describing measurement techniques, examples of EIT images are presented. Noting that EIT suffers from the ill-posed nature of the corresponding inverse problem, Magnetic Resonance Electrical Impedance Tomography (MREIT) has been proposed to provide images with better spatial resolution and accuracy. MREIT utilizes internal information on the induced magnetic field in addition to the boundary measurements. Mathematical theory, algorithms, and experimental results of current MREIT research are described. As another way of handling the ill-posedness in EIT, lesion estimation techniques have been suggested. Assuming that a lesion has a different conductivity and/or permittivity compared with normal tissues, the lesion estimation including its location and size estimate could be a well-posed problem. Introducing mathematical models, lesion estimation algorithms, and measurement techniques, some of experimental results are explained. At the end of the chapter, potential applications of EIT and MREIT are discussed. Breast cancer detection is taken as the primary application area of the lesion estimation techniques.

Keywords: Electrical impedance tomography; static imaging; MREIT;