Publications:Intelligent vocal cord image analysis for categorizing laryngeal diseases

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Title Intelligent vocal cord image analysis for categorizing laryngeal diseases
Author
Year 2005
PublicationType Conference Paper
Journal
HostPublication Innovations in applied artificial intelligence
Conference 18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA/AIE 2005
DOI http://dx.doi.org/10.1007/11504894_11
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:300233
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.