Publications:Intelligent vocal cord image analysis for categorizing laryngeal diseases
From ISLAB/CAISR
| Title | Intelligent vocal cord image analysis for categorizing laryngeal diseases |
|---|---|
| Author | Antanas Verikas and Adas Gelzinis and Marija Bacauskiene and Virgilijus Uloza |
| 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. |
