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Principal Component Analysis And Artificial Neural Network Analysis of Oral Tissue Fluorescence Spectra: Classification of Normal Premalignant And Malignant Pathological Conditions

Nayak, GS and Kamath, Sai Giridhar and Pai, Keerthilatha M and Sarkar, A and Ray, S and Kurien, J and D'Almeida, L and Krishnanand, BR and Santhosh, C and Kartha, VB and Mahato, KK (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.

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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
Uncontrolled Keywords: Oral tissue,Laser induced flouresence,Principal companent analysis,Artificial neural network.
Subjects: Dentistry > MCODS Manipal > Oral Medicine and Radiology
Life Sciences > MLSC Manipal
Medicine > KMC Manipal > Pathology
Medicine > KMC Manipal > Surgical Oncology
Depositing User: KMC Manipal
Date Deposited: 30 Sep 2011 06:48
Last Modified: 08 Oct 2013 06:29
URI: http://eprints.manipal.edu/id/eprint/1458

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