Optical Microscope Image Processing for Automated Cells Counting

Abstract

With growth of nano-bio industry, it is of significant importance to develop an automated system to exploit cell behaviors, including migration, mitosis, apoptosis, shape deformation of individual cells and their interactions among cells in the process of cell growth. In this paper, we proposed preprocessing techniques, a classification method which classifies clusters (overlapping multiple cells) from cells and an automated method which counts the number of cells and clusters in order to analyze 2D or 3D deformations of the cells in the real-time images from microscope in the cell culture. We conducted the 3T3 cell images taken from each thirty-minute interval. It showed the average 99.8% accuracy automatically for separating cells and clusters.