• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1699-1704
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• 2009

If detected early enough, cervical cantor may have a good survival rate due to its preneoplastic state. However, the process is so time consuming that a medical expert can handle only a small amount of such examinations. In this paper, we propose a new nucleus extraction algorithm for uterine cervical pap smears in order to mitigate such burdens of medical experts. In the preneoplastic state cytodiagnosis images, it is important to differentiate three main areas - background, cytoplasm and nucleus. Thus, we apply lighting compensation and $3{\times}3$ mask of B channel in order to restore damaged image and remove noises respectively. The cell object is obtained from those clean binarized images with Grossfire algorithm. When there are clusters of cells, the target nucleus can be obtained with repetitive binarization of R channel brightness. In our experiment of using uterine cervical pap smears of 400 magnifications that is common in the diagnostic cytology, our method is able to extract 40 nucleus out of 45 population successfully.