Systematic quantification of cell confluence in human normal oral fibroblasts

Ching Hsiang Chiu, Jyh Der Leu, Tzu Ting Lin, Pin Hua Su, Wan Chun Li, Yi Jang Lee*, Da Chuan Cheng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Background: The accurate determination of cell confluence is a critical step for generating reasonable results of designed experiments in cell biological studies. However, the cell confluence of the same culture may be diversely predicted by individual researchers. Herein, we designed a systematic quantification scheme implemented on the Matlab platform, the so-called “Confluence-Viewer” program, to assist cell biologists to better determine the cell confluence. Methods: Human normal oral fibroblasts (hOFs) seeded in 10 cm culture dishes were visualized under an inverted microscope for the acquisition of cell images. The images were subjected to the cell segmentation algorithm with top-hat transformation and the Otsu thresholding technique. A regression model was built using a quadratic model and shape-preserving piecewise cubic model. Results: The cell segmentation algorithm generated a regression curve that was highly correlated with the cell confluence determined by experienced researchers. However, the correlation was low when compared to the cell confluence determined by novice students. Interestingly, the cell confluence determined by experienced researchers became more diverse when they checked the same images without a time limitation (up to 1 min). Conclusion: This tool could prevent unnecessary human-made mistakes and meaningless repeats for novice researchers working on cell-based studies in health care or cancer research.

Original languageEnglish
Article number9146
Pages (from-to)1-12
Number of pages12
JournalApplied Sciences (Switzerland)
Issue number24
StatePublished - 2 Dec 2020


  • Cell confluence
  • Confluence-viewer
  • Human normal oral fibroblasts
  • Systematic quantification


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