Prototype-based classification

Image-based diagnostic tools are important tools for the determination of diseases in many medical applications. The interpretation of these images is often done manually, based on prototypical images. Consequently, only a few images collected into an image catalogue are initially available as a basis for the development of an automatic image-interpretation system. In this paper we study the question if it is possible to build up an image-interpretation system based on such an image catalogue. We call the system catalogue-based image classifier. The system is provided with feature-subset selection, feature weighting, and prototype selection. The performance of the catalogue-based classifier is assessed by studying the accuracy and the reduction of the prototypes after applying a prototype-selection algorithm. We describe the results that could be achieved and give an outlook for further developments on a catalogue-based classifier.