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Pseudo Color Features Extraction technique for cervical cancer of Pap smear images

Cervix cancer is the most common gynecological malignancy and second most common cancer among female in Malaysia after breast cancer. The objective of this study is to extract the size of nucleus and cytoplasm, as well as gray level values of cervical cells from ThinPrep images so that accurate value of those parameters can easily be obtained. An alternative approach of extracting features for Pap smear cytology images i.e., by using Seed Based Region Growing technique and Pseudo Coloring is proposed in this study. The technique is called Pseudo Color Feature Extraction (PCFE). A correlation test is applied between data extracted using the proposed algorithm and data extracted manually by cytotechnologists. The technique operates well on cervical cells images with correlation values approaching 1.0 which indicates a strong positive correlation. The strongest relationship is the size of cytoplasm with correlation factor of 0.988595 and the next strongest relationship is its gray level with correlation factor of 0.981534. Such results indicate that the proposed technique is suitable and has high capability to be used as an image extraction technique for extracting cervical cells features as well as acts as a filter and a segmentation tool. This would assist cytopathologists and cytotechnologists in the cervical cancer screening process by providing accurate value of size and gray level of nucleus and cytoplasmic features.