A new method for blood cell image segmentation and counting based on PCNN and autowave
Su Mao-jun, Wang Zhao-bin, Hongjuan Zhang, Yide Ma · 2008
In the field of biomedicine, because of cells’ complex nature, it still remains a challenging task to segment cells from its background and count them automatically. The Pulse-Coupled Neural Network (PCNN) has been shown to be a very powerful image processing tool, so, in this paper, after studying the autowave characteristic of PCNN and morphology we present a new method for blood cell image segmentation and counting. The method can not only de-noise and segment blood cell image perfectly, but also can well eliminate disturbed objects which will serious impact the blood cell counting step, and is able to segment specific isolated cell from its background. Experimental results show that the algorithm is effective and the results are desirable.