The Method of Segmentation of Cervical Nuclei in Complex Background - ZHAO Jing; LIANG Long-kai; HE Yong-jun; XIE Yi-ning (Journal of Harbin University of Science and Technology)
Automatic screening technology developed in recent years. It applies image processing, and first recognizes nucleus and then measures the DNA contents accurately, so it can provide auxiliary for a doctor′s diagnosis. Image segmentation is the key technique of automatic screening system which directly determines the performance of the systems. However, the imaging environments under the microscope are complex. One the one hand, uneven illumination, background shading and uneven dyed nucleus exist. On the other hand, there are inevitably blood cells, lymphocytes, garbage, impurities and conglobation cells in cell images. These conditions degrade the performance of image segmentation. In order to solve these problems, we put forward a method to segment cervical nuclei in complex background. This method first employs the local threshold method to segment images. In this procedure we propose a parameter adapting method which adjusts its parameters automatically according to the function of local threshold window size and the binarized outline number. The local threshold method transforms an image into a binary image which is then passed to image corrosion operator to generate a marking image. With the binary image, the watershed algorithm was finally performed to segment the image. The experiment shows that the method can adapt to the complex image environment and separate the cells with lower overlapping nuclei images.