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Bioinformatics of lung cancer

Stefanie Marotta, Zervakis Michalis, Aditi Deshpande, Sarhan Musa, Livanos, Georges, Ying Na, Tannaz Farrahi

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URI: http://purl.tuc.gr/dl/dias/D5E1628D-D28B-4625-B716-23236262A96F
Year 2015
Type of Item Conference Full Paper
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Bibliographic Citation G.C.Giakos, S. Marotta, S. Shrestha, A. Deshpande, T. Farrahi, L. Zhang, T. Cambria, A. Blinzler, T. Quang, Y. Na, G. Livanos, M. Zervakis, S. Musa ,"Bioinformatics of lung canver ,"in 2015 Intern. Conf. on Imaging Syst. and Techniques (IST) ,pp,1-6.doi:10.1109/IST.2015.7294524 https://doi.org/10.1109/IST.2015.7294524
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Conference Publications in Community School of Electrical and Computer Engineering

Summary

The objective of this study is to explore novel bioinformatics techniques, namely, the Polarimetric Exploratory Data Analysis (pEDA), for early identification and discrimination of precancerous and cancerous lung tissues. The outcome of this study indicates that the full-width-at half maximum (FWHM) and Dynamic Range (DR) extracted from histograms of inherent (label-free) near infrared (NIR) diffused-polarimetric reflectance signals provide an important metrics for the characterization of cancerous tissue. Application of pEDA on the acquired data has been proved an effective diagnostic tool aimed at discriminating optical information among normal, precancerous, and cancerous lung tissue samples. Therefore, it can eventually be proved a useful diagnostic tool in the early detection of Non-Small Cell Lung Cancer (NSCLC) as well as in classical cytopathology and histopathology.

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