Graph walks for classification of histopathological images
Author
Olgun, Gülden
Sokmensuer, C.
Gündüz-Demir, Çiğdem
Date
2013Source Title
2013 IEEE 10th International Symposium on Biomedical Imaging
Publisher
IEEE
Pages
1126 - 1129
Language
English
Type
Conference PaperItem Usage Stats
126
views
views
98
downloads
downloads
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.
Keywords
GraphsAutomated cancer diagnosis
Graphs
Histopathological image analysis
Subgraphs
Medical imaging
Tissue
Tissue engineering
Image classification