
Proceedings Paper
A graphical approach for x-ray image representation and categorizationFormat | Member Price | Non-Member Price |
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Paper Abstract
Medical Image databases are a key component in future diagnosis and preventive medicine. Automatic categorization of
medical images plays an important role for structuring of given medical databases as well as for searching and retrieval
of medical images. This paper focuses on a general framework for efficient representation and classification of X-ray
images, appropriate for medical image archives. The proposed methodology is comprised of a graph theoretic image
representation scheme and image matching measures. In this work, x-ray images are represented by undirected graphs
and categorization is done based on an inexact graph matching scheme, graph edit distance. Initially, an unsupervised
clustering algorithm is applied on input x-ray images in order to extract coherent regions in feature space, and
corresponding coherent segments in the image content. The segmented images are then represented as graphs, which are
used in the image matching process. Finally, the experimental results have also been presented at the end of the paper.
Paper Details
Date Published: 26 February 2010
PDF: 7 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 754612 (26 February 2010); doi: 10.1117/12.855091
Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)
PDF: 7 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 754612 (26 February 2010); doi: 10.1117/12.855091
Show Author Affiliations
Chhanda Ray, RCC Institute of Information Technology (India)
Sankar Narayan Das, Jadavpur Univ. (India)
Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)
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