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In this paper, a novel method for automated diagnosis of cervical cancer by extracting cytoplasm and nuclei from cervical cytology images is described. The background is removed by preprocessing methods like Edge sharpening and Adaptive Histogram Equalization. Fuzzy thresholding and Active contours are used for extracting the region of interest containing the cytoplasm and nuclei. The nuclei are separated from the cytoplasm using linear contrast stretching. The nucleus to cytoplasm ratio is used to determine the stage of cancer. General Terms Image Processing, Cervical Cancer

Automated Extraction of Cytoplasm and Nuclei from Cervical Cytology Images by Fuzzy Thresholding and Active Contours