Adaptive weighted vector means optimization for healthy and malignant skin modeling at microwave frequencies using clinical data

Article

Awal, Md Abdul, Naqvi, Syed Akbar Raza, Foong, Damien and Abbosh, Amin. 2024. "Adaptive weighted vector means optimization for healthy and malignant skin modeling at microwave frequencies using clinical data." IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology. 8 (2), pp. 170-181. https://doi.org/10.1109/JERM.2024.3374090
Article Title

Adaptive weighted vector means optimization for healthy and malignant skin modeling at microwave frequencies using clinical data

ERA Journal ID212745
Article CategoryArticle
AuthorsAwal, Md Abdul, Naqvi, Syed Akbar Raza, Foong, Damien and Abbosh, Amin
Journal TitleIEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology
Journal Citation8 (2), pp. 170-181
Number of Pages12
Year2024
PublisherIEEE (Institute of Electrical and Electronics Engineers)
Place of PublicationUnited States
ISSN2469-7249
2469-7257
Digital Object Identifier (DOI)https://doi.org/10.1109/JERM.2024.3374090
Web Address (URL)https://ieeexplore.ieee.org/abstract/document/10478913
Abstract

The dielectric properties of normal and cancerous skin vary with frequency due to changes in water content and tissue composition. Developing a reliable microwave system for skin cancer detection requires accurate characterization of that change in the dielectric properties. A possible choice is the Cole-Cole model, which can accurately fit the measured dielectric data for tissues. However, fitting the non-linear Cole-Cole model parameters with the measured data requires a sophisticated optimization algorithm. This study proposes an adaptive weighted vector means optimization algorithm, which employs adaptive initialization, logarithmic spaces, and enhanced local search mechanism, resulting in improved accuracy with fewer iterations. The algorithm is evaluated using dielectric data from healthy skin, basal cell carcinoma, squamous cell carcinoma, and melanoma and is found to outperform other relevant algorithms. One of the salient features of this study is that a set of clinical melanoma dielectric data is acquired, analyzed, and physically interpreted in terms of relaxation frequency and dispersion across 0.3 GHz to 14 GHz. It is found that melanoma closely follows the second-order Debye model, which is a special case for the second-order Cole-Cole model with a zero-valued dispersion broadening parameter. Although melanoma data is obtained from one lesion because of the low incidence rate, the research findings will contribute to a better understanding skin cancer at microwave frequencies. A triangular plot, which shows model fitness accuracy and the number of iterations, is presented to summarize the advantages of the algorithm.

KeywordsAdaptive weighted vector means optimization; Cole-Cole model; dielectric measurements; skin cancer; specific absorption rate
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020400399. Biomedical engineering not elsewhere classified
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Byline AffiliationsUniversity of Queensland
Mylab, Australia
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