Intelligent vocal cord image analysis for categorizing laryngeal diseases

Authors:
Antanas Verikas;Adas Gelzinis;Marija Bacauskiene;Virgilijus Uloza
Affiliations:
Department of Applied Electronics, Kaunas University of Technology, Kaunas, Lithuania and Intelligent Systems Laboratory, Halmstad University, Halmstad, Sweden;Department of Applied Electronics, Kaunas University of Technology, Kaunas, Lithuania;Department of Applied Electronics, Kaunas University of Technology, Kaunas, Lithuania;Kaunas University of Medicine, Kaunas, Lithuania
Venue:
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Year:
2005

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Abstract

Colour, shape, geometry, contrast, irregularity and roughness of the visual appearance of vocal cords are the main visual features used by a physician to diagnose laryngeal diseases. This type of examination is rather subjective and to a great extent depends on physician's experience. A decision support system for automated analysis of vocal cord images, created exploiting numerous vocal cord images can be a valuable tool enabling increased reliability of the analysis, and decreased intra- and inter-observer variability. This paper is concerned with such a system for analysis of vocal cord images. Colour, texture, and geometrical features are used to extract relevant information. A committee of artificial neural networks is then employed for performing the categorization of vocal cord images into healthy, diffuse, and nodular classes. A correct classification rate of over 93% was obtained when testing the system on 785 vocal cord images.We gratefully acknowledge the support we have received from the Lithuanian State Science and Studies Foundation.