Segmentasi Citra Sel Tunggal Smear Serviks Menggunakan Radiating Component Normalized Generalized GVFS

Abstract

Component Normalized Generalized Gradient Vector Flow Snake (CNGGVFS) method is the development of Gradient Vector Flow Snake (GVFS) method as an external force algorithm for active contour (snake) that can be used to get the contour of nucleus and cytoplasm of cervical smear image. However, CNGGVFS using a conventional calculation of edge map such as Sobel can not detect the nucleus area correctly in single cell cervical smear image segmentation. In this study, an external force algorithm in snake that uses Radiating Edge Map (REM) calculation to search the edge map in CNGGVFS, called as Radiating Component Normalized Generalized Gradient Vector Flow Snake (RCNGGVFS), is proposed. RCNGGVFS is used to get the contour of nucleus and cytoplasm of single cervical smear image. There are three main stages in this study, which are: pre-processing, initial segmentation, and contour segmentation. Experiments are conducted on Herlev data-set. The proposed method is compared with other methods in previous research in single cell cervical smear image segmentation. The experiment results show that the proposed method can detect the nucleus area correctly better than Radiating GVFS & Fuzzy C-Means (FCM) and Radiating GVFS & K-means. The average value of accuracy and Zijdenbos similarity index (ZSI) for nucleus segmentation is 95.34% and 88.06%. Then, the average value of accuracy and ZSI for cytoplasm segmentation is 83.48% and 87.16%. The evaluations show the proposed method can be used as a segmentation process of cervical smear image on automatic identification of cervical cancer.