Publications:Categorizing sequences of laryngeal data for decision support
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| Title | Categorizing sequences of laryngeal data for decision support |
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| Author | |
| Year | 2009 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | ECT 2009 : Electrical and Control Technologies |
| Conference | 4th International Conference on Electrical and Control Technologies, ECT 2009, Kaunas University of Technology, Kaunas, Lithuania, 7-8 May 2009 |
| DOI | |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:1193130 |
| Abstract | This paper is concerned with kernel-based techniques for categorizing laryngeal disorders based on information extracted from sequences of laryngeal colour images. The features used to characterize a laryngeal image are given by the kernel principal components computed using the N-vector of the 3-D colour histogram. The least squares support vector machine (LS-SVM) is designed for categorizing an image sequence into the healthy, nodular and diffuse classes. The kernel function employed by the SVM classifier is defined over a pair of matrices, rather than over a pair of vectors. An encouraging classification performance was obtained when testing the developed tools on data recorded during routine laryngeal videostroboscopy. |
