Optimised analytical models of the dielectric properties of biological tissue

•A novel two-stage genetic algorithm is applied to optimize 54 types of human tissues.•The performance of the proposed two-stage GA has been compared with five other optimization techniques.•Most accurate values of three-pole Debye model parameters for 54 tissue types, over the frequency range of 50...

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Vydané v:Medical engineering & physics Ročník 43; s. 103 - 111
Hlavní autori: Salahuddin, Saqib, Porter, Emily, Krewer, Finn, O’ Halloran, Martin
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England Elsevier Ltd 01.05.2017
Predmet:
Algorithms
Dielectric properties
Electric Impedance
Genetic algorithm
Least-Squares Analysis
Models, Biological
Optimisation
Parametric models
Radiology
Optimisation
Genetic algorithm
Parametric models
Dielectric properties
ISSN:1350-4533, 1873-4030, 1873-4030
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Shrnutí:•A novel two-stage genetic algorithm is applied to optimize 54 types of human tissues.•The performance of the proposed two-stage GA has been compared with five other optimization techniques.•Most accurate values of three-pole Debye model parameters for 54 tissue types, over the frequency range of 500 MHz to 20 GHz, are presented for reference. The interaction of electromagnetic fields with the human body is quantified by the dielectric properties of biological tissues. These properties are incorporated into complex numerical simulations using parametric models such as Debye and Cole-Cole, for the computational investigation of electromagnetic wave propagation within the body. These parameters can be acquired through a variety of optimisation algorithms to achieve an accurate fit to measured data sets. A number of different optimisation techniques have been proposed, but these are often limited by the requirement for initial value estimations or by the large overall error (often up to several percentage points). In this work, a novel two-stage genetic algorithm proposed by the authors is applied to optimise the multi-pole Debye parameters for 54 types of human tissues. The performance of the two-stage genetic algorithm has been examined through a comparison with five other existing algorithms. The experimental results demonstrate that the two-stage genetic algorithm produces an accurate fit to a range of experimental data and efficiently out-performs all other optimisation algorithms under consideration. Accurate values of the three-pole Debye models for 54 types of human tissues, over 500 MHz to 20 GHz, are also presented for reference.
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ISSN:1350-4533
1873-4030
1873-4030
DOI:10.1016/j.medengphy.2017.01.017