Automated image processing to quantify cell migration

Abstract

Methods to evaluate migration capacity of stem cells and the inhibition by chemicals are important for biomedical research. Here, we established an automated image processing framework to quantify migration of human neural crest (NC) cells into an initially empty, circular region of interest (ROI). The ROI is partially filled during the experiment by migrating cells. Based on an image captured only once at the end of the biological experiment, the framework identifies the initial ROI. The identification worked also, when the distribution of surrounding cells showed large heterogeneity. After segmentation, the number of migrated cells was identified. The image processing framework was capable of efficiently quantifying chemical effects on cell migration.