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      Altçizge modellemesi kullanarak kolon bez tespiti

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      Author
      Özgül, Etkin Barış
      Sökmensüer, C.
      Gündüz-Demir, Çiğdem
      Date
      2011-04
      Source Title
      IEEE 19th Signal Processing and Communications Applications Conference, SIU 2011
      Publisher
      IEEE
      Pages
      726 - 729
      Language
      Turkish
      Type
      Conference Paper
      Item Usage Stats
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      Abstract
      Kolon adenokarsinomu, kolon bez yapılarında değişimlere yol açar. Patologlar bezlerdeki bu değişimleri değerlendirerek kolon adenokarsinom tanı ve derecelendirmesi yaparlar. Ancak değişimlerin değerlendirme süreci kaydadeğer öznellik taşıyabilir. Bezlerin matematiksel özniteliklerle karakterize edilmesiyle bu öznelliği azaltabilmek olasıdır. Bunun içinse ilk aşama, bezlerin yerlerinin otomatik olarak tespit edilmesidir. Literatürdeki bez tespit etme yöntemleri çoğunlukla piksel tabanlıdır. Ancak doku görüntüleri, doğaları gereği ve biyopsi hazırlama ve görüntü alma işlemlerindeki değişkenlik nedeni ile piksel bazında değişkenlik gösterebilir. Öte yandan, bu değişkenliğe rağmen, bezleri oluşturan doku bileşenlerinin uzaysal dağılımı benzer özellik gösterir. Bu dağılımı gözönüne alarak tasarlanan yöntemler, bölütleme başarısını artırma potansiyeline sahiptir. Bu çalışmada önerdiğimiz yöntem, ilk olarak, doku bileşenlerinin dağılımını, bu bileşenler üzerinde oluşturduğu bir çizge ile modeller. Daha sonra, oluşturduğu bu çizgeyi altçizgelere ayırır ve bu altçizgelerin öznitelikleri yardımıyla bezleri tespit eder. Kolon doku görüntüleri üzerinde yaptığımız çalışmalar, önerilen bu yöntemin bezlerin yüksek doğrulukta tespit edilmesinde umut verici sonuçlar verdiğini göstermiştir. The colon adenocarcinoma causes changes in glandular structures of colon tissues. Pathologists assess these changes to diagnose and grade the colon adenocarcinoma. However, this assessment may consist of a considerable amount of subjectivity. It is possible to reduce this subjectivity by characterizing the glands with mathematical features. For that, the first step is to detect gland locations. In literature, most of the gland detection methods are pixel-based. However, tissue images may show pixel-level variances due to their nature and differences in biopsy preparation and image acquisition procedures. On the other hand, in spite of these variances, the distribution of tissue components forming glands show similar properties. The methods that consider this distribution has the potential of improving the performance. The method proposed in this study first models the distribution of the components by constructing a graph on them. Then, it breaks the constructed graph down into subgraphs and detects the glands using the features of these subgraphs. The experiments conducted on colon tissue images show that the proposed method leads to promising results for detecting the glands. © 2011 IEEE.
      Keywords
      Colon tissue images
      Colon tissues
      Detection methods
      Glandular structures
      Subgraphs
      Tissue components
      Tissue images
      Pixels
      Tissue
      Signal detection
      Permalink
      http://hdl.handle.net/11693/28386
      Published Version (Please cite this version)
      https://doi.org/10.1109/SIU.2011.5929753
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      • Department of Computer Engineering 1368
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