Towards non-invasive diagnosis of skin cancer: Sensing depth investigation of open-ended coaxial probes

Cemanur Aydinalp, Sulayman Joof, Tuba Yilmaz*

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Makalebilirkişi

15 Atıf (Scopus)

Özet

Dielectric properties of biological tissues are traditionally measured with open-ended coaxial probes. Despite being commercially available for laboratory use, the technique suffers from high measurement error. This prevents the practical applications of the open-ended coaxial probes. One such application is the utilization of the technique for skin cancer detection. To enable a diagnostic tool, there is a need to address the error sources. Among others, tissue heterogeneity is a major contributor to measurement error. The effect of tissue heterogeneity on measurement accuracy can be decreased by quantifying the probe sensing depth. To this end, this work (1) investigates the sensing depth of the 2.2 mm-diameter open-ended coaxial probe for skin mimicking material and (2) offers a simple experimental setup and protocol for sensing depth characterization of open-ended coaxial probes. The sensing depth characterized through simulation and experiments using two double-layered configurations composed to mimic the skin tissue heterogeneity. Three thresholds in percent increase of dielectric property measurements were chosen to determine the sensing depth. Based on the experiment results, it was concluded that the sensing depth was effected by the dielectric property contrast between the layers. That is, high contrast results in rapid change whereas low contrast results in a slower change in measured dielectric properties. It was also concluded that the sensing depth was independent of frequency between 0.5 to 6 GHz and was mostly determined by the material located immediately at the aperture of the probe.

Orijinal dilİngilizce
Makale numarası1319
Sayfa (başlangıç-bitiş)1-19
Sayfa sayısı19
DergiSensors
Hacim21
Basın numarası4
DOI'lar
Yayın durumuYayınlandı - 2 Şub 2021

Bibliyografik not

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Finansman

This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska–Curie grant agreement No. 750346 and the Istanbul Technical University under grant agreement 41554. We would like to acknowledge the valuable contribution provided by Mehmet Nuri Akinci and Ismail Dilman for the in-house algorithm used in the paper.

FinansörlerFinansör numarası
Horizon 2020 Framework Programme750346
Istanbul Teknik Üniversitesi41554

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