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.
Kata Kunci: Radiating Component Normalized Generalized Gradient Vector
Flow Snake, sel tunggal smear serviks, ekstraksi kontur
Penulis: Nursuci Putri Husain,
Chastine Fatichah
Kode Jurnal: jptlisetrodd170466
