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      Automatic segmentation of colon glands using object-graphs

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      Author
      Gunduz Demir, C.
      Kandemir, M.
      Tosun, A. B.
      Sokmensuer, C.
      Date
      2010
      Source Title
      Medical Image Analysis
      Print ISSN
      1361-8415
      Publisher
      Elsevier BV
      Volume
      14
      Issue
      1
      Pages
      1 - 12
      Language
      English
      Type
      Article
      Item Usage Stats
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      209
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      Abstract
      Gland segmentation is an important step to automate the analysis of biopsies that contain glandular structures. However, this remains a challenging problem as the variation in staining, fixation, and sectioning procedures lead to a considerable amount of artifacts and variances in tissue sections, which may result in huge variances in gland appearances. In this work, we report a new approach for gland segmentation. This approach decomposes the tissue image into a set of primitive objects and segments glands making use of the organizational properties of these objects, which are quantified with the definition of object-graphs. As opposed to the previous literature, the proposed approach employs the object-based information for the gland segmentation problem, instead of using the pixel-based information alone. Working with the images of colon tissues, our experiments demonstrate that the proposed object-graph approach yields high segmentation accuracies for the training and test sets and significantly improves the segmentation performance of its pixel-based counterparts. The experiments also show that the object-based structure of the proposed approach provides more tolerance to artifacts and variances in tissues. © 2009 Elsevier B.V. All rights reserved.
      Keywords
      Attributed graphs
      Colon adenocarcinoma
      Gland segmentation
      Histopathological image analysis
      Image segmentation
      Object - graphs
      Permalink
      http://hdl.handle.net/11693/22441
      Published Version (Please cite this version)
      http://dx.doi.org/10.1016/j.media.2009.09.001
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