Graph walks for classification of histopathological images

Date
2013
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Source Title
2013 IEEE 10th International Symposium on Biomedical Imaging
Print ISSN
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Publisher
IEEE
Volume
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Pages
1126 - 1129
Language
English
Type
Conference Paper
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Abstract

This paper reports a new structural approach for automated classification of histopathological tissue images. It has two main contributions: First, unlike previous structural approaches that use a single graph for representing a tissue image, it proposes to obtain a set of subgraphs through graph walking and use these subgraphs in representing the image. Second, it proposes to characterize subgraphs by directly using distribution of their edges, instead of employing conventional global graph features, and use these characterizations in classification. Our experiments on colon tissue images reveal that the proposed structural approach is effective to obtain high accuracies in tissue image classification. © 2013 IEEE.

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Keywords
Graphs, Automated cancer diagnosis, Graphs, Histopathological image analysis, Subgraphs, Medical imaging, Tissue, Tissue engineering, Image classification
Citation
Published Version (Please cite this version)