A Guideline for Complex Permittivity Retrieval of Tissue-Mimicking Phantoms From Open-Ended Coaxial Probe Response With Deep Learning

Sulayman Joof*, Cemanur Aydinalp, Ismail Dilman, Mehmet Nuri Akinci, Tuba Yilmaz, Mehmet Cayoren, Ibrahim Akduman

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7 Atıf (Scopus)

Özet

In this work, we proposed a general guideline and a technique for retrieving the complex permittivities (CPs) of material under test (MUT) from the measured reflection coefficients (RCs) obtained with the open-ended coaxial probe (OECP) through a deep learning model (DLM). Particularly, lossy materials such as phantoms mimicking the biological tissues are considered as MUT in this study. The dataset used to design (train, validate, and test) the DLM is synthetically generated using the relationship between the CPs of the MUT, namely, admittance model, and the four-pole Cole-Cole relaxation model. Moreover, the technique is implemented to accurately predict the CPs of biological tissues with real measured RCs' data from 0.5 to 20 GHz with a 50-MHz resolution. This technique eliminates the need to physically perform measurements required to create the dataset for DLM and it can be easily implemented for real-time CPs' measurement of biological tissues. The designed DLM is initially trained, validated, and tested with 80%, 10%, and 10% of the total generated synthetic dataset, respectively. A percent relative error of 1.5 ± 0.88% is obtained for CPs' prediction at the test stage. Furthermore, DLM is tested with real RCs' data measured from four different tissue-mimicking phantoms: skin, muscle, blood, and fat. Predicted CPs from DLM are compared with the CPs' results obtained from a commercially available OECP measurement kit. A (mean) ± (std.dev) percent relative error ranging from 2.08 ± 0.4 to 10.84 ± 2.43 within the frequency band of interest was obtained after comparison.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)5105-5115
Sayfa sayısı11
DergiIEEE Transactions on Microwave Theory and Techniques
Hacim70
Basın numarası11
DOI'lar
Yayın durumuYayınlandı - 1 Kas 2022

Bibliyografik not

Publisher Copyright:
© 1963-2012 IEEE.

Finansman

This work was supported by the Health Institutes of Turkiye through the Turkiye Saglik Enstituleri Baskanligi (TuSEB) under Agreement 22724.

FinansörlerFinansör numarası
Health Institutes of Turkiye
Turkiye Saglik Enstituleri Baskanligi22724

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