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A kernel-based approach to categorizing laryngeal images
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0003-2185-8973
Department of Applied Electronics, Kaunas University of Technology, Lithuania.
Department of Applied Electronics, Kaunas University of Technology, Lithuania.
Department of Applied Electronics, Kaunas University of Technology, Lithuania.
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2007 (English)In: Computerized Medical Imaging and Graphics, ISSN 0895-6111, E-ISSN 1879-0771, Vol. 31, no 8, p. 587-594Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
New York: Pergamon Press, 2007. Vol. 31, no 8, p. 587-594
Keywords [en]
Laryngeal image, Colour, Texture, Gabor filtering, Co-occurrence matrix, Support vector machine
National Category
Engineering and Technology Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:hh:diva-1320DOI: 10.1016/j.compmedimag.2007.07.003ISI: 000251486400001PubMedID: 17714915Scopus ID: 2-s2.0-35348938961Local ID: 2082/1699OAI: oai:DiVA.org:hh-1320DiVA, id: diva2:238538
Available from: 2008-04-15 Created: 2008-04-15 Last updated: 2017-12-13Bibliographically approved

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Verikas, Antanas

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf