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This work presents a mathematical framework of a new microscopic electrical impedance tomography (micro-EIT) system which aims to pro¬duce cross-sectional conductivity images of a biological tissue sample or cells inside a small hexahedral container. Unlike conventional micro-EIT systems which have much in common with a standard EIT system, the proposed micro-EIT system has a unique electrode configuration and associated data collection method. Two sides of the container facing each other are fully covered by driving electrodes. Injecting current between this driving electrode pair, we can create a uniform parallel current density distribution inside the container when it is filled with a homogeneous saline. We install many miniature electrodes on the other two sides and the bottom of the container for voltage measurements. The top of the container is open for sample manipulations. This electrode configuration provides a large number of voltage measurements from the three surfaces subject to one current injection. In this paper, we provides a mathematical framework of this novel micro-EIT system for the development of image re-construction algorithms. Taking advantage of the uniform parallel current density, we construct an inversion formula of the conductivity from the acquired boundary voltage. Employing the reciprocity theorem for the electrode configuration, we compute a sensitivity matrix to reconstruct cross-sectional conductivity images. Numerical simulations show that the proposed algorithm successfully reconstructs conductivity images of multiple anomalies. In terms of the image quality, the new micro-EIT system is advantageous over a conventional EIT method adopting multiple current injection patterns. For experimental studies to be followed, we suggest micro-EIT system developments based on the proposed novel idea.

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Abstract
Introduction
Projected Conductivity Image Reconstruction
Sensitivity Matrix Approach
References

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UCI(KEPA) : I410-ECN-0101-2013-410-000845806