The Potential of the Double Debye Parameters to Discriminate between Basal Cell Carcinoma and Normal Skin

Bao C Q Truong, Hoang Duong Tuan, Vincent P. Wallace, Anthony J. Fitzgerald, Hung T. Nguyen

    Research output: Contribution to journalArticle

    14 Citations (Scopus)

    Abstract

    The potential of terahertz imaging for improving the efficiency of Mohs's micrographic surgery in terms of tumor margin detection was previously studied. Thanks to high water content of human skin, its dielectric response to terahertz radiation can be described by the double Debye model which uses five parameters to fit experimental data. Skin tumors typically have a higher water content than normal tissues do, and this should be apparent in the parameters. The goal of this paper is to apply statistical methods to these parameters to test their power to differentiate skin cancer from normal tissue. Based on the prediction accuracy estimated using a cross-validation method, we found the best classifier was the static permittivity at low frequency (εs). By combining the most relevant parameters, we obtained a classification accuracy of 95.7%, confirming the classification capability of the parameters, thereby supporting their application to improve terahertz imaging for the purpose of skin cancer delineation.

    Original languageEnglish
    Article number7302086
    Pages (from-to)990-998
    Number of pages9
    JournalIEEE Transactions on Terahertz Science and Technology
    Volume5
    Issue number6
    Early online date26 Oct 2015
    DOIs
    Publication statusPublished - 1 Nov 2015

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