Abstract
Cells are highly dynamic, changing shape through stretching or contracting, moving and dividing. Recent advances in computational image analysis allow for quantification of cellular dynamics, but there does not exist a robust and consistent process. The purpose of our work was to create a process with image analysis software to measure changes in cell area and perimeter over time, then create a mathematical model to predict the amount of tension present in the cell membrane. Our work uses ImageJ, with a machine learning plugin, WEKA to identify and quantify cell membranes from experimental time lapses.
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