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Proceedings Paper

Recurrence quantification as potential bio-markers for diagnosis of pre-cancer
Author(s): Sabyasachi Mukhopadhyay; Sawon Pratiher; Ritwik Barman; Souvik Pratiher; Asima Pradhan; Nirmalya Ghosh; Prasanta K. Panigrahi
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Paper Abstract

In this paper, the spectroscopy signals have been analyzed in recurrence plots (RP), and extract recurrence quantification analysis (RQA) parameters from the RP in order to classify the tissues into normal and different precancerous grades. Three RQA parameters have been quantified in order to extract the important features in the spectroscopy data. These features have been fed to different classifiers for classification. Simulation results validate the efficacy of the recurrence quantification as potential bio-markers for diagnosis of pre-cancer.

Paper Details

Date Published: 3 March 2017
PDF: 5 pages
Proc. SPIE 10063, Dynamics and Fluctuations in Biomedical Photonics XIV, 1006310 (3 March 2017); doi: 10.1117/12.2251235
Show Author Affiliations
Sabyasachi Mukhopadhyay, Indian Institute of Science Education and Research Kolkata (India)
Sawon Pratiher, Indian Institute of Technology Kanpur (India)
Ritwik Barman, Indian Institute of Science Education and Research Kolkata (India)
Souvik Pratiher, KIIT Univ. (India)
Asima Pradhan, Indian Institute of Technology Kanpur (India)
Nirmalya Ghosh, Indian Institute of Science Education and Research Kolkata (India)
Prasanta K. Panigrahi, Indian Institute of Science Education and Research Kolkata (India)


Published in SPIE Proceedings Vol. 10063:
Dynamics and Fluctuations in Biomedical Photonics XIV
Valery V. Tuchin; Kirill V. Larin; Martin J. Leahy; Ruikang K. Wang, Editor(s)

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