Parameter estimation method of the biological tissue equivalent circuit model for local EIT
Abstract
Tissue impedance in beta dispersion region is expected to offer useful information for tissue structures, physiological states and functions. In short, electrical impedance tomography (EIT) is a technique that can reconstruct image of electrical impedance spatial distribution noninvasively in a biological tissue. Therefore, EIT is able not only to present information of tissue structure as well as existing Xray computer tomography (CT), magnetic resonance imaging (MRI), ultrasound, and other medical imaging methods but also to give useful information of tissue function for diagnosis. However, there are several problems to achieve the practical use of EIT, which are an inverse algorithm for estimating parameters, and electrode configuration and so on.
In our recent studies, we has proposed a new configuration of the electrodes, called “divided electrode”, for a highspeed measurement of bio-impedance in a cross section of a local tissue.
The purpose of this study is to fundamentally investigate parameter estimation algorithm of the spatial distribution from measured impedance data. In this study, the cross section of the tissue was represented by spatial distributed equivalent circuits of tissue structure known, and their parameters were estimated by inverse algorithm. Models take account of tumor and contact impedance caused when measuring it. Estimation of impedance parameter is carried out by use of the Gauss-Newton method. As a result of the evaluation computer simulations, it is found from that the proposed method is very useful and practical as a new local tissue EIT technology.
Keywords
divided electrode bio-impedance parameter estimation Gauss-Newton methodPreview
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