Publications:Image analysis based categorization of laryngeal diseases

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Title Image analysis based categorization of laryngeal diseases
Author Donatas Valincius and Antanas Verikas and Adas Gelzinis and Marija Bacauskiene
Year 2006
PublicationType Conference Paper
Journal
HostPublication Proceedings of the 1st International Conference on Electrical and Control Technologies, 2006
Conference 1st International Conference on Electrical and Control Technologies, 2006, MAY 04-05, 2006 Kaunas, LITHUANIA, 2006
DOI
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:577047
Abstract This paper concentrates on an automated analysis of laryngeal images aiming to categorize the images into three decision classes, namely healthy, nodular and diffuse. The problem is treated as an amage analysis and classification task. To obtain a comprehensive description of laryngeal images, multiple feature sets exploiting information on image colour, texture, geometry, image intensity gradient direction, and frequency content are extracted. A separate support vector machine (SVM) is used to categorize features of each type into decision classes. The final image categorization is then obtained which is based on the decisions provided by a committee of support vector machines. Bearing in mind a high similarity of the decision classes, the correct classification rate of over 94 % is obtained while testing the system on 785 laryngeal images that are recorded by the Department of Otolaryngology, Kaunas University of Medicine is rather promising.