An image analysis tool for cell migration assay with a large sample size

Di Yin; Hongbo Zhang; Shih-Mo Yang; Ruixue Yin; Wenjun Zhang

doi:10.1117/12.2667479

28 March 2023 An image analysis tool for cell migration assay with a large sample size

Di Yin, Hongbo Zhang, Shih-Mo Yang, Ruixue Yin, Wenjun Zhang

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125661Y (2023) https://doi.org/10.1117/12.2667479
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

Cell migration assay is the most common research approach for cell migration. Quantitative research and analysis are carried out by measuring the migration of cells into the region that is artificially created among confluent monolayer cells. To improve the efficiency and accuracy of the analysis, the software/tools were developed to assist the image analysis process. However, these software and tools are still at the stage of measuring a single sample, which cannot satisfy the requirement of large sample size for cell migration assay device. In this paper, an image analysis tool based on Fiji is developed, which can segment multiple samples from a scanned image and then analyze a single sample in batch. In addition, the screening function should be added for the application scenario of large sample size. The samples can be filtered according to different conditions to improve the consistency of experimental conditions. The results show that the developed analysis tool ATCA has high accuracy in identifying cell-free zones, with a difference of 2.3% from the tool WHST and 2.9% from manual operation. The analysis efficiency of this tool is 15 times that of manual operation.

Citation Download Citation

Di Yin, Hongbo Zhang, Shih-Mo Yang, Ruixue Yin, and Wenjun Zhang "An image analysis tool for cell migration assay with a large sample size", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125661Y (28 March 2023); https://doi.org/10.1117/12.2667479

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