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Proceedings Paper

Early stage detection of precancer using variational mode decomposition and artificial neural network
Author(s): Sawon Pratiher; Sabyasachi Mukhopadhyay; Souvik Hazra; Ritwik Barman; Gautham Pasupuleti; Nirmalya Ghosh; Prasanta K. Panigrahi
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Paper Abstract

In this contribution, combined variational mode decomposition (VMD) aided non-linear feature descriptors & artificial neural network (ANN) for identification of different healthy and precancerous cervical tissues. Owing to the inherent problems of background laser system noise interferences in elastic scattering spectroscopic data, VMD method being noise robust is of paramount interest. VMD is used to decompose the normalized spectral data into 2 modes for analysis and attributes extraction. For each of these VMD separated modes, non-linear entropy and multifractal features, namely Shannon entropy (SE), Renyi entropy (RE), Tsallis entropy (TE) and Singularity spectrum width (SSW) are extracted to form the feature set. The extracted features are subjected to analysis of variance (ANOVA) test for subsequent feature ranking & selection of the statistically most significant features. The designated features are trained with ANN to classify the backscattered tissue spectra into healthy and cancerous ones.

Paper Details

Date Published: 17 May 2018
PDF: 5 pages
Proc. SPIE 10685, Biophotonics: Photonic Solutions for Better Health Care VI, 1068523 (17 May 2018); doi: 10.1117/12.2307278
Show Author Affiliations
Sawon Pratiher, Indian Institute of Technology Kharagpur (India)
Sabyasachi Mukhopadhyay, Indian Institute of Science Education and Research Kolkata (India)
Souvik Hazra, EURECOM (France)
Ritwik Barman, Indian Institute of Science Education and Research Kolkata (India)
Gautham Pasupuleti, Biodesign Innovation Labs. Private Limited (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. 10685:
Biophotonics: Photonic Solutions for Better Health Care VI
Jürgen Popp; Valery V. Tuchin; Francesco Saverio Pavone, Editor(s)

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