Amir, R. and Elham Shakibapour and Lalitha, R. (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, 2013.
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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 Library Assistant |
| Date Deposited: | 11 Nov 2019 07:12 |
| Last Modified: | 16 Jul 2022 07:28 |
| URI: | http://eprints.uni-mysore.ac.in/id/eprint/9615 |
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