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Biomedical subjects

Bong Seok Kim

Publications and source records attributed to Bong Seok Kim.

3 recordsLinked to original sources

Reducing boundary effects in static EIT imaging.

Electrical impedance tomography (EIT) is a non-invasive technique used to image the electrical conductivity and permittivity within a body from measurements taken on the body's surface. High-quality static images are required for many medical imaging applications. Forming such images usually requires an accurate way to calculate the expected voltages on the surface resulting from the application of known currents to that surface. This is described as the forward problem. This paper introduces a new method to improve static images by using an improved forward solution which estimates a different conductivity value for each applied current pattern. This method, creating an automatically adjusting forward solution, can improve the sensitivity of static images under many EIT imaging applications. It does so by reducing the boundary effects caused by electrodes and any layered structures near them such as skin. The drawback of this method is that circularly symmetric structures of interest may be suppressed or eliminated from the images. The performance of this method is illustrated in a 2D circular phantom with simulation data from both a FEM model and experimental data.

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Dynamic electrical impedance imaging of a chest phantom using the Kalman filter.

A dynamic complex impedance imaging technique is developed with the aid of the linearized Kalman filter (LKF) for real-time reconstruction of the human chest. The forward problem is solved by an analytical method based on the separation of variables and Fourier series. The inverse problem is treated as a state estimation problem. The nonlinear measurement equation is linearized about the best homogeneous impedivity value as an initial guess, and the impedivity distribution is estimated with the aid of the Kalman estimator. The Kalman gain matrix is pre-computed and stored off-line to minimize the on-line computational time. Simulation and phantom experiment are reported to illustrate the reconstruction performances in the sense of spatio-temporal resolution in a simplified geometry of the human chest.

Algorithms↗

Dynamic electrical impedance imaging with the interacting multiple model scheme.

In this paper, an effective dynamical EIT imaging scheme is presented for on-line monitoring of the abruptly changing resistivity distribution inside the object, based on the interacting multiple model (IMM) algorithm. The inverse problem is treated as a stochastic nonlinear state estimation problem with the time-varying resistivity (state) being estimated on-line with the aid of the IMM algorithm. In the design of the IMM algorithm multiple models with different process noise covariance are incorporated to reduce the modeling uncertainty. Simulations and phantom experiments are provided to illustrate the proposed algorithm.

Algorithms↗