Updated 7 Nov 2020
Background: Accurate determination of cell confluence is a critical step for generating reasonable results of designed experiments in cell biological studies. However, cell confluence of the same culture may be diversely predicted by individual researchers. Here we designed a systematic quantification scheme implemented on the Matlab platform, so called “confluence viewer” program to assist the cell biologists who could better determine the cell confluence. Methods: Human normal oral fibroblasts (hOFs) seeded in 10-cm culture dishes were visualized under an inverted microscope for acquisition of cell images. The images were subjected to the cell segmentation algorithm with the top-hat transformation and the Otsu thresholding technique. The regression model was built by a quadratic model and shape-preserving piecewise cubic model. Results: The cell segmentation algorithm generated a highly correlated regression curve with the cell confluence determined by senior researchers. However, the correlation was low compared to the cell confluence determined by rookie students. Interestingly, the cell confluence determined by senior researchers would become more diverse when they checked the same images without time limitation (up to 1 minute). Conclusion: This tool would avoid unnecessary human-made mistakes and meaningless repeats for rookie researchers working on cell-based studies in health care or cancer research.
Da-Chuan Cheng (2023). Confluence viewer (https://www.mathworks.com/matlabcentral/fileexchange/82370-confluence-viewer), MATLAB Central File Exchange. Retrieved .
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