Symbolic representation over skeleton endpoints for classification of medical X-ray images

Rajaei, A. and Dallalzadeh, E. and Rangarajan, L. (2013) Symbolic representation over skeleton endpoints for classification of medical X-ray images. In: ICPRAM 2013 - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods.

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Abstract

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 skeleton endpoints are localized. A complete directed graph is then constructed over the skeleton endpoints. Subsequently, distance and orientation features are extracted from the constructed graph. Further, shape features based on skeleton endpoints are also extracted. The obtained features are used to form an interval valued feature vector. Finally, a symbolic classifier is explored to classify medical X-ray body organ images. Our proposed model is simple and efficient.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Pattern recognition, Symbolic representation, Medical imaging, Feature vectors, Graph-cut segmentations, Graphic methods, Image classification, Image segmentation, Interval-valued, Medical X-rays, Orientation features, Medical X-ray image, Musculoskeletal system, Skeleton endpoints
Subjects: D Physical Science > Computer Science
Divisions: Department of > Computer Science
Depositing User: Arshiya Kousar
Date Deposited: 11 Nov 2019 07:12
Last Modified: 11 Nov 2019 07:12
URI: http://eprints.uni-mysore.ac.in/id/eprint/9615

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