Recognition of living abnormal cells based on an optical microscope

A method is presented to monitor and analyze tumor cells' biological process by image processing techniques based on an optical microscope in this paper. Meanwhile, the hybrid operation combination of the micro and nano manipulation plays a crucial role in studying living cells' biological process and the interactions of cells and drugs. In this paper, we propose an improved image segmentation method which can be used for the recognition of living abnormal cells. We segment cell images using a threshold segmentation algorithm, combining an improved boundary breakpoint connection algorithm with an improved hole filling algorithm. The method was tested using images from an inverted light microscope. Experimental results demonstrate that the elapsed time of the whole recognition process is about 10 seconds, and the recognition rate is high.