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      • Department of Computer Engineering
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      Unsupervised tissue image segmentation through object-oriented texture

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      Author
      Tosun, Akif Burak
      Sokmensuer, C.
      Gündüz-Demir, Çiğdem
      Date
      2010
      Source Title
      2010 20th International Conference on Pattern Recognition
      Print ISSN
      1051-4651
      Publisher
      IEEE
      Pages
      2516 - 2519
      Language
      English
      Type
      Conference Paper
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      Abstract
      This paper presents a new algorithm for the unsupervised segmentation of tissue images. It relies on using the spatial information of cytological tissue components. As opposed to the previous study, it does not only use this information in defining its homogeneity measures, but it also uses it in its region growing process. This algorithm has been implemented and tested. Its visual and quantitative results are compared with the previous study. The results show that the proposed segmentation algorithm is more robust in giving better accuracies with less number of segmented regions. © 2010 IEEE.
      Keywords
      Image segmentation
      Quantitative medical image analysis
      Texture analysis
      Medical image analysis
      Object oriented
      Quantitative result
      Region growing
      Segmentation algorithms
      Segmented regions
      Spatial informations
      Texture analysis
      Tissue components
      Tissue image segmentation
      Tissue images
      Unsupervised segmentation
      Algorithms
      Image analysis
      Information use
      Medical imaging
      Pattern recognition
      Textures
      Tissue
      Image segmentation
      Permalink
      http://hdl.handle.net/11693/28520
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/ICPR.2010.616
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      • Department of Computer Engineering 1368
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