Classification of dental lesions fluorescence spectra using support vector machine method

I. S. Atanasov; Ekaterina G. Borisova; O. I. Yordanov; Tzonko T. Uzunov; Lachezar A. Avramov

doi:10.1117/12.618812

22 April 2005 Classification of dental lesions fluorescence spectra using support vector machine method

I. S. Atanasov, Ekaterina G. Borisova, O. I. Yordanov, Tzonko T. Uzunov, Lachezar A. Avramov

Proceedings Volume 5830, 13th International School on Quantum Electronics: Laser Physics and Applications; (2005) https://doi.org/10.1117/12.618812
Event: 13th International School on Quantum Electronics: Laser Physics and Applications, 2004, Bourgas, Bulgaria

Abstract

We use the Support Vector Machine method to distinguish fluorescence spectra obtained from demineralized teeth from those obtained from healthy teeth. We find intervals of values for the various parameters of the algorithm, such as dimension, degree of smoothness, etc, as to achieve at least 90% diagnostic accuracy. We argue that the success of the methodology is determined by its multidimensional nature.

Citation Download Citation

I. S. Atanasov, Ekaterina G. Borisova, O. I. Yordanov, Tzonko T. Uzunov, and Lachezar A. Avramov "Classification of dental lesions fluorescence spectra using support vector machine method", Proc. SPIE 5830, 13th International School on Quantum Electronics: Laser Physics and Applications, (22 April 2005); https://doi.org/10.1117/12.618812

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