Adaptive local thresholding for detection of nuclei in diversity stained cytology images

Accurate cell nucleus segmentation is necessary for automated cytological image analysis. Thresholding is a crucial step in segmentation. The accuracy of segmentation depends on the accuracy of thresholding. In this paper we propose a new method for thresholding of photomicrographs of diversly stained cytology smears. To account for the different stains, we use different color spaces. A new local thresholding scheme is developed to solve the problem of nonuniform staining. Finally, the results obtained from the new method are compared with those of some of the existing thresholding methods, clearly showing the improvement achieved.