]> 2026-04-04T17:13:44+02:00 Publications:Categorizing laryngeal images for decision support 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/10.1007/978-3-540-74607-2_47 http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:239283 530 Advanced Concepts for Intelligent Vision Systems : 9th International Conference, ACIVS 2007, Delft, The Netherlands, August 28-31, 2007 ; proceedings Book Chapter Lecture Notes in Computer Science ; Volume 4678/2007 521 Categorizing laryngeal images for decision support 2007 2016-09-30T20:41:24Z 2457662.3620833 Categorizing laryngeal images for decision support 500 0 plainlist list 1 [[:Publications:Categorizing laryngeal images for decision support]] Categorizing laryngeal images for decision support# QUERY0576b10bb3c9fa620ed3cd2432edf2f7 500 [2,"smw-datavalue-property-restricted-annotation-use","Publisher"] Categorizing laryngeal images for decision support# ERR6c155b5d70b69ddb590b4f2e73389c2a 500 [2,"smw-datavalue-property-restricted-annotation-use","Author"] Categorizing laryngeal images for decision support# ERRe24f17e090c98448f3de99d03182b7b6