Principal component analysis and artificial neural network analysis of oral tissue fluorescence spectra: classification of normal premalignant and malignant pathological conditions

Nayak, G. S. ; Kamath, Sudha ; Pai, Keerthilatha M. ; Sarkar, Arindam ; Ray, Satadru ; Kurien, Jacob ; D'Almeida, Lawrence ; Krishnanand, B. R. ; Santhosh, C. ; Kartha, V. B. ; Mahato, K. K. (2006) Principal component analysis and artificial neural network analysis of oral tissue fluorescence spectra: classification of normal premalignant and malignant pathological conditions Biopolymers, 82 (2). pp. 152-166. ISSN 0006-3525

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Official URL: http://onlinelibrary.wiley.com/doi/10.1002/bip.204...

Related URL: http://dx.doi.org/10.1002/bip.20473

Abstract

Pulsed laser-induced autofluorescence spectroscopic studies of pathologically certified normal, premalignant, and malignant oral tissues were carried out at 325 nm excitation. The spectral analysis and classification for discrimination among normal, premalignant, and malignant conditions were performed using principal component analysis (PCA) and artificial neural network (ANN) separately on the same set of spectral data. In case of PCA, spectral residuals, Mahalanobis distance, and scores of factors were used for discrimination among normal, premalignant, and malignant cases. In ANN, parameters like mean, spectral residual, standard deviation, and total energy were used to train the network. The ANN used in this study is a classical multiplayer feed-forward type with a back-propagation algorithm for the training of the network. The specificity and sensitivity were determined in both classification schemes. In the case of PCA, they are 100 and 92.9%, respectively, whereas for ANN they are 100 and 96.5% for the data set considered.

Item Type:Article
Source:Copyright of this article belongs to John Wiley and Sons, Inc.
Keywords:Oral Tissue; Laser-induced Fluorescence; Principal Component Analysis; Artificial Neural Network
ID Code:17904
Deposited On:16 Nov 2010 13:22
Last Modified:03 Jun 2011 11:12

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