High correlation of double Debye model parameters in skin cancer detection

Truong, BCQ; Tuan, HD; Fitzgerald, AJ; Wallace, VP; Nguyen, HT

High correlation of double Debye model parameters in skin cancer detection

Truong, BCQ Tuan, HD

Fitzgerald, AJ Wallace, VP Nguyen, HT

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Publication Type:: Conference Proceeding
Citation:: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, 2014, pp. 718 - 721
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Truong, BCQ	en_US
dc.contributor.author	Tuan, HD https://orcid.org/0000-0003-0292-6061	en_US
dc.contributor.author	Fitzgerald, AJ	en_US
dc.contributor.author	Wallace, VP	en_US
dc.contributor.author	Nguyen, HT https://orcid.org/0000-0003-3373-8178	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014, 2014, pp. 718 - 721	en_US
dc.identifier.isbn	9781424479290	en_US
dc.identifier.uri	http://hdl.handle.net/10453/33399
dc.description.abstract	© 2014 IEEE. The double Debye model can be used to capture the dielectric response of human skin in terahertz regime due to high water content in the tissue. The increased water proportion is widely considered as a biomarker of carcinogenesis, which gives rise of using this model in skin cancer detection. Therefore, the goal of this paper is to provide a specific analysis of the double Debye parameters in terms of non-melanoma skin cancer classification. Pearson correlation is applied to investigate the sensitivity of these parameters and their combinations to the variation in tumor percentage of skin samples. The most sensitive parameters are then assessed by using the receiver operating characteristic (ROC) plot to confirm their potential of classifying tumor from normal skin. Our positive outcomes support further steps to clinical application of terahertz imaging in skin cancer delineation.	en_US
dc.relation.ispartof	2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014	en_US
dc.relation.isbasedon	10.1109/EMBC.2014.6943691	en_US
dc.subject.mesh	Skin	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Carcinoma, Basal Cell	en_US
dc.subject.mesh	Skin Neoplasms	en_US
dc.subject.mesh	ROC Curve	en_US
dc.subject.mesh	Models, Theoretical	en_US
dc.subject.mesh	Terahertz Spectroscopy	en_US
dc.subject.mesh	Biomarkers, Tumor	en_US
dc.title	High correlation of double Debye model parameters in skin cancer detection	en_US
dc.type	Conference Proceeding
utslib.for	0903 Biomedical Engineering	en_US
dc.location.activity	Chicago, US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. The double Debye model can be used to capture the dielectric response of human skin in terahertz regime due to high water content in the tissue. The increased water proportion is widely considered as a biomarker of carcinogenesis, which gives rise of using this model in skin cancer detection. Therefore, the goal of this paper is to provide a specific analysis of the double Debye parameters in terms of non-melanoma skin cancer classification. Pearson correlation is applied to investigate the sensitivity of these parameters and their combinations to the variation in tumor percentage of skin samples. The most sensitive parameters are then assessed by using the receiver operating characteristic (ROC) plot to confirm their potential of classifying tumor from normal skin. Our positive outcomes support further steps to clinical application of terahertz imaging in skin cancer delineation.

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http://hdl.handle.net/10453/33399