Symbolic features for classification of medical X-ray body organ images

In this paper, we propose a model for symbolic representation and classification of medical X-ray body organ images. Medical X-ray body organ images are segmented using graph cut segmentation method. Based on the boundary of a segmented body organ image, the geometric centroid points are localized. A complete directed graph is then constructed over the centroid points. Subsequently, distance and orientation features are extracted from the constructed graph. The obtained features are used to form an interval valued feature vector representation. Finally, a symbolic classifier is explored to classify medical X-ray body organ images. Our proposed model is simple and efficient.