Characterization and classification of oral tissues using excitation and emission matrix: a statistical modeling approach

Udayakumar Kanniyappan; Einstein Gnanatheepaminstein; Aruna Prakasarao; Koteeswaran Dornadula; Ganesan Singaravelu

doi:10.1117/12.2255872

17 February 2017 Characterization and classification of oral tissues using excitation and emission matrix: a statistical modeling approach

Udayakumar Kanniyappan, Einstein Gnanatheepaminstein, Aruna Prakasarao, Koteeswaran Dornadula, Ganesan Singaravelu

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Proceedings Volume 10060, Optical Biopsy XV: Toward Real-Time Spectroscopic Imaging and Diagnosis; 100601E (2017) https://doi.org/10.1117/12.2255872
Event: SPIE BiOS, 2017, San Francisco, California, United States

Abstract

Cancer is one of the most common human threats around the world and diagnosis based on optical spectroscopy especially fluorescence technique has been established as the standard approach among scientist to explore the biochemical and morphological changes in tissues. In this regard, the present work aims to extract spectral signatures of the various fluorophores present in oral tissues using parallel factor analysis (PARAFAC). Subsequently, the statistical analysis also to be performed to show its diagnostic potential in distinguishing malignant, premalignant from normal oral tissues. Hence, the present study may lead to the possible and/or alternative tool for oral cancer diagnosis.

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Udayakumar Kanniyappan, Einstein Gnanatheepaminstein, Aruna Prakasarao, Koteeswaran Dornadula, and Ganesan Singaravelu "Characterization and classification of oral tissues using excitation and emission matrix: a statistical modeling approach", Proc. SPIE 10060, Optical Biopsy XV: Toward Real-Time Spectroscopic Imaging and Diagnosis, 100601E (17 February 2017); https://doi.org/10.1117/12.2255872

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KEYWORDS

Tissues

Cancer

Statistical analysis

Diagnostics

Luminescence

Data modeling

Fluorescence spectroscopy

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