Segmentation of Live and Dead Cells in Tissue Scaffolds

Uyar T., Erdamar A., Aksahin M. F., GÜMÜŞDERELİOĞLU M., Irmak G., Erogul O.

26th IEEE Signal Processing and Communications Applications Conference (SIU), İzmir, Turkey, 2 - 05 May 2018 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2018.8404384
  • City: İzmir
  • Country: Turkey
  • Gazi University Affiliated: No


Image processing techniques are frequently used for extracting quantitative information (cell area, cell size, cell counting, etc.) from different types of microscopic images. Image analysis in the field of cell biology and tissue engineering is time consuming, and requires personal expertise. In addition, evaluation of the results may be subjective. Therefore, computerbased learning / vision-based applications have been developed rapidly in recent years. In this study, images of the viable pre-osteoblastic mouse MC3T3-E1 cells in tissue scaffolds, which was captured from a bone tissue regeneration study, were analyzed by using image processing techniques. Tissue scaffolds were bioprinted from alginate and alginate-hydroxyapatite polymers. Confocal Laser Scanning Microscope images of the tissue scaffolds were processed in the study. Percentages of live and dead cell area in the scaffolds were determined by using image processing techniques at two different time points of the culture.