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Proceedings Paper

Autofluorescence spectroscopy for early diagnosis of cancer eye
Author(s): Shovan K. Majumder; Nirmalya Ghosh; Sopan M. Rathod; Pradeep K. Gupta
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Paper Abstract

We report an in-vitro autofluorescence spectroscopic study of cow eye tissue to explore the applicability of the approach in discriminating early stage "cancer eye" from normal squamous eye tissues. Significant differences were observed in the autofluorescence signatures between the "cancer eye" and normal eye tissues. The spectral differences were quantified by employing a probability-based diagnostic algorithm developed based on recently formulated theory of Relevance Vector Machine (RVM), a Bayesian machine-learning framework of statistical pattern recognition. The algorithm provided sensitivity and specificity values of 97 ± 2% towards cancer for the training set data based on leave-one-out cross validation and a sensitivity of 97 ± 2% and a specificity of 99 ± 1% towards cancer for the independent validation set data. These results suggest that autofluorescence spectroscopy might prove to be a quantitative in-vivo diagnostic modality for early and accurate diagnosis of "cancer eye" in veterinary clinical setting, which would help improve ranch management from both economic and animal care standpoint.

Paper Details

Date Published: 6 February 2007
PDF: 9 pages
Proc. SPIE 6430, Advanced Biomedical and Clinical Diagnostic Systems V, 64301K (6 February 2007); doi: 10.1117/12.724874
Show Author Affiliations
Shovan K. Majumder, Vanderbilt Univ. (United States)
Nirmalya Ghosh, Raja Ramanna Ctr. for Advanced Technology (India)
Sopan M. Rathod, Abasaheb Garware College (India)
Pradeep K. Gupta, Raja Ramanna Ctr. for Advanced Technology (India)

Published in SPIE Proceedings Vol. 6430:
Advanced Biomedical and Clinical Diagnostic Systems V
Ramesh Raghavachari; Tuan Vo-Dinh; Warren S. Grundfest; David A. Benaron; Gerald E. Cohn, Editor(s)

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