Publications:Towards video laryngostroboscopy-based automated screening for laryngeal disorders

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Title Towards video laryngostroboscopy-based automated screening for laryngeal disorders
Author Adas Gelzinis and Evaldas Vaiciukynas and Edgaras Kelertas and Bacauskiene Marija and Antanas Verikas and Uloza Virgilijus and Vegiene Aurelija
Year 2009
PublicationType Conference Paper
Journal
HostPublication Proceedings of the 6th International Conference “Models and Analysis of Vocal Emissions for Biomedical Applications”, MAVEBA 2009
Conference 6th International Conference “Models and Analysis of Vocal Emissions for Biomedical Applications”, MAVEBA 2009, December 14-16, Firenze, Italy
DOI
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:284996
Abstract This paper is concerned with kernel-based techniques for automatedcategorization of laryngeal colour image sequences obtained by videolaryngostroboscopy. Features used to characterize a laryngeal imageare given by the kernel principal components computed using the$N$-vector of the 3-D colour histogram. The least squares supportvector machine (LS-SVM) is designed for categorizing an imagesequence (video) into the healthy, cancerous and noncancerous classes. The kernel function employed by theLS-SVM is defined over a pair of matrices, rather than over a pairof vectors. The classification accuracy of over 85% was obtainedwhen testing the developed tools on data recorded during routinelaryngeal videostroboscopy.