• A Resampling-Based Markovian Model For Automated Colon Cancer Diagnosis 

      Özdemir, Erdem; Sokmensuer, Cenk; Gunduz-Demir, Cigdem (Ieee-Inst Electrical Electronics Engineers Inc, 2012)
      In recent years, there has been a great effort in the research of implementing automated diagnostic systems for tissue images. One major challenge in this implementation is to design systems that are robust to image ...
    • Local Object Patterns for the Representation and Classification of Colon Tissue Images 

      Olgun, Gulden; Sokmensuer, Cenk; Gunduz-Demir, Cigdem (Ieee-Inst Electrical Electronics Engineers Inc, 2014)
      This paper presents a new approach for the effective representation and classification of images of histopathological colon tissues stained with hematoxylin and eosin. In this approach, we propose to decompose a tissue ...
    • Multilevel Segmentation Of Histopathological Images Using Cooccurrence Of Tissue Objects 

      Simsek, Ahmet Cagri; Tosun, Akif Burak; Aykanat, Cevdet; Sokmensuer, Cenk; Gunduz-Demir, Cigdem (Ieee-Inst Electrical Electronics Engineers Inc, 2012)
      This paper presents a new approach for unsupervised segmentation of histopathological tissue images. This approach has two main contributions. First, it introduces a new set of high-level texture features to represent the ...
    • Two-Tier Tissue Decomposition For Histopathological Image Representation And Classification 

      Gultekin, Tunc; Koyuncu, Can Fahrettin; Sokmensuer, Cenk; Gunduz-Demir, Cigdem (Ieee-Inst Electrical Electronics Engineers Inc, 2015)
      In digital pathology, devising effective image representations is crucial to design robust automated diagnosis systems. To this end, many studies have proposed to develop object-based representations, instead of directly ...