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Modeling human head tissues using fourth-order debye model in convolution-based three-dimensional finite-difference time-domain

Abstract

A fourth order Debye model is derived using genetic algorithms to represent the dispersive properties of the 17 tissues that form the human head. The derived model gives accurate estimation of the electrical properties of those tissues across the frequency band from 0.1 GHz to 3 GHz that can be used in microwave systems for head imaging. A convolution-based three-dimensional finite-difference time-domain (3D-FDTD) formulation is implemented for modeling the electromagnetic wave propagation in the dispersive head tissues whose frequency dependent properties are represented by the derived fourth-order Debye model. The presented results show that the proposed 3D-FDTD and fourth-order Debye model can accurately show the electromagnetic interaction between a wide band radiation and head tissues with low computational overhead and more accurate results compared with using multi-pole Cole-Cole model

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