]> 2026-04-04T18:04:15+02:00 Publications:A kernel-based approach to categorizing laryngeal images 500 en <p>This paper is concerned with an approach to automated analysis of vocal fold images aiming to categorize laryngeal diseases. Colour, texture, and geometrical features are used to extract relevant information. A committee of support vector machines is then employed for performing the categorization of vocal fold images into healthy, diffuse, and nodular classes. The discrimination power of both, the original and the space obtained based on the kernel principal component analysis is investigated. A correct classification rate of over 92% was obtained when testing the system on 785 vocal fold images. Bearing in mind the high similarity of the decision classes, the correct classification rate obtained is rather encouraging.</p> http://dx.doi.org/10.1016/j.compmedimag.2007.07.003 http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:238538 594 8 Computerized Medical Imaging and Graphics Journal Paper 587 A kernel-based approach to categorizing laryngeal images 31 2007 2016-09-30T20:39:17Z 2457662.3606134 A kernel-based approach to categorizing laryngeal images 500 0 plainlist list 1 [[:Publications:A kernel-based approach to categorizing laryngeal images]] A kernel-based approach to categorizing laryngeal images# QUERYc8d09229ae1be33e0131f4ca8e26b7bd 500 [2,"smw-datavalue-property-restricted-annotation-use","Publisher"] A kernel-based approach to categorizing laryngeal images# ERR6c155b5d70b69ddb590b4f2e73389c2a 500 [2,"smw-datavalue-property-restricted-annotation-use","Author"] A kernel-based approach to categorizing laryngeal images# ERRe24f17e090c98448f3de99d03182b7b6