Automated recognition and measurement of cell morphology on optically-induced electrokinetic patterning chip

Cell behaviors including adhesion, migration, proliferation, differentiation and apoptosis, etc. deeply influence tissue formation, regeneration, and even the function of whole tissue or entity. Optically-induced electrokinetic (OEK) patterning is an efficient method to guide cells to grow and form the desired structure on a substrate and hence becomes an effective approach to the study of cell behaviors. But recognition and measurement of large number of cells are challengeable. In this study, automated recognition and measurement of cellular geometric features on the patterned substrate using the OEK method is proposed in which the recognition of cells is realized by segmenting individual cells from the microscope image using snake computation model with dynamic programming and the geometric features such as area, perimeter, semi-major axis and orientation angle are extracted for the study of cell behaviors. The relation between the geometric features and cell behaviors has been studied. The automated system can recognize and measure the geometric features of cells rapidly, accurately and efficiently, and bring more convenience for development of biology and life science.