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Proceedings Paper

Integrated quantitative fractal polarimetric analysis of monolayer lung cancer cells
Author(s): Suman Shrestha; Lin Zhang; Tri Quang; Tannaz Farrahi; Chaya Narayan; Aditi Deshpande; Ying Na; Adam Blinzler; Junyu Ma; Bo Liu; George C. Giakos
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Paper Abstract

Digital diagnostic pathology has become one of the most valuable and convenient advancements in technology over the past years. It allows us to acquire, store and analyze pathological information from the images of histological and immunohistochemical glass slides which are scanned to create digital slides. In this study, efficient fractal, wavelet-based polarimetric techniques for histological analysis of monolayer lung cancer cells will be introduced and different monolayer cancer lines will be studied. The outcome of this study indicates that application of fractal, wavelet polarimetric principles towards the analysis of squamous carcinoma and adenocarcinoma cancer cell lines may be proved extremely useful in discriminating among healthy and lung cancer cells as well as differentiating among different lung cancer cells.

Paper Details

Date Published: 21 May 2014
PDF: 18 pages
Proc. SPIE 9099, Polarization: Measurement, Analysis, and Remote Sensing XI, 90990T (21 May 2014); doi: 10.1117/12.2053596
Show Author Affiliations
Suman Shrestha, The Univ. of Akron (United States)
Univ. of Massachusetts Medical School (United States)
Lin Zhang, Cleveland State Univ. (United States)
Tri Quang, The Univ. of Akron (United States)
Tannaz Farrahi, The Univ. of Akron (United States)
Chaya Narayan, The Univ. of Akron (United States)
Aditi Deshpande, The Univ. of Akron (United States)
Ying Na, Hangzhou Dianzi Univ. (China)
Adam Blinzler, The Univ. of Akron (United States)
Junyu Ma, The Ohio State Univ. (United States)
Bo Liu, The Univ. of Akron (United States)
George C. Giakos, The Univ. of Akron (United States)


Published in SPIE Proceedings Vol. 9099:
Polarization: Measurement, Analysis, and Remote Sensing XI
David B. Chenault; Dennis H. Goldstein, Editor(s)

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