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Abstract
Leucocyte segmentation is one of the most crucial functionalities for an automatic leucocyte recognition system. In this paper, an algorithm is proposed to segment the leucocytes from the overlapping cell images. It consists of two main steps. The first step involves generation of a combined image based on the saturation and green channels (CIBSGC) by means of the different distribution characteristics of the leucocyte nucleus. A weight coefficient is used to adjust the CIBSGC for extracting the nucleus and estimating the location of the leucocyte. Second, a method of phase detection and spiral interpolation identifies the overlapping regions of cells and determines the leucocyte edge curve. The performance is evaluated by three parameters: sensitivity, positive predictive value and pixel number error. Experimental results validate that the proposed algorithm can successfully segment the overlapping leucocyte with the satisfactory performance for two cell image datasets under different recording conditions.
Acknowledgements
This work was supported by the Programme for New Century Excellent Talents in University (NCET) of China (NCET-07-0735), the Natural Science Foundation of Hebei, China (F2009001638) and the National Natural Science Foundation of China (61071200). The authors would particularly like to thank Chongqing Tianhai Medical Equipment, Co., Ltd. for providing the microscopic cell images. This work was supported by the Programme for New Century Excellent Talents in University (NCET) of China (NCET-07-0735), Natural Science Foundation of Hebei, China (F2009001638). The authors would particularly like to thank Chongqing Tianhai Medical Equipment, Co., Ltd. for providing the microscopic cell images.