Now showing items 1-4 of 4

    • Carcinoma cell line discrimination in microscopic images using unbalanced wavelets 

      Keskin F.; Suhre, A.; Erşahin, T.; Çetin-Atalay R.; Çetin, A. E. (2012)
      Cancer cell lines are widely used for research purposes in laboratories all over the world. In this paper, we present a novel method for cancer cell line image classification, which is very costly by conventional methods. ...
    • Smart markers for watershed-based cell segmentation 

      Koyuncu, Can Fahrettin (Bilkent University, 2012)
      Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the ...
    • A supervised learning model for live cell segmentation 

      Koyuncu, C.F.; Durmaz I.; Cetin-Atalay, R.; Gunduz-Demir, C. (IEEE Computer Society, 2014)
      Automated cell imaging systems have been proposed for faster and more reliable analysis of biological events at the cellular level. The first step of these systems is usually cell segmentation whose success affects the ...
    • Unsupervised segmentation of live cell images using gaussian modeling 

      Arslan, S.; Durmaz, I.; Çetin-Atalay R.; Gündüz-Demir, C. (2011)
      The first step of targeted cancer drug development is to screen and determine drug candidates by in vitro measuring the effectiveness of the drugs. The tests developed for this purpose can be time consuming due to their ...