Time-lapse microscopy imaging serves as an important method to measure the cycle progression of individual cells in a large population. The lacking of automatic systems that can deal with large volume of time-lapse optical microscopy imaging is a bottleneck of modern bio-imaging research. In this paper we present an effective computerized method for overlapping cell nuclei detection in time-lapse image sequences. We design a two-stage detection scheme for such cells in each image of the image sequence. Features of the skeleton and the contour of the cell model are extracted in the two stages, and overlapped cells are detected by the similarity of the features with the training samples. Experimental results shows the proposed method is very effective and the work shows great assistance for the cell nuclei segmentation afterward.
['Ding Jie', 'Lu Jing-feng', 'Yang Jing-yu']
Combined Technologies in Analysis of Overlapping Cells