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      • Department of Computer Engineering
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      Graph walks for classification of histopathological images

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      Author
      Olgun, Gülden
      Sokmensuer, C.
      Gündüz-Demir, Çiğdem
      Date
      2013
      Source Title
      2013 IEEE 10th International Symposium on Biomedical Imaging
      Publisher
      IEEE
      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.
      Keywords
      Graphs
      Automated cancer diagnosis
      Graphs
      Histopathological image analysis
      Subgraphs
      Medical imaging
      Tissue
      Tissue engineering
      Image classification
      Permalink
      http://hdl.handle.net/11693/27983
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/ISBI.2013.6556677
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