Pap Smear Images Segmentation for Automatic Detection of Cervical Cancer
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 4)Publication Date: 2015-04-05
Authors : Ayubu Hassan Mbaga; Pei ZhiJun;
Page : 940-943
Keywords : Cervical cancer; Segmentation; Canny; MGLGD;
- Stratigraphy and Structural Geology of Ciuyah Mud Volcanoes in Ciniru Area,West Java
- Geology Structure Identification Using Pre-Stack Depth Migration (PSDM) Method of Tomography Result in North West Java Basin
- Geomorphological Characteristics of Rancaekek Area, Sumedang Regency, West Java
- Drainage Pattern Characteristics of Jatinangor Area, Sumedang Regency, West Java
- Drainage Analysis of Cihea Area, Haurwangi Subdistrict, Cianjur Regency, West Java
Abstract
This work focuses on segmentation of Pap smear cervical cell image for automatic screening and detection of cervical cancer at early stage. This paper proposed linear contrast enhancement and median filter for removing of noise, sharpens and preserving edges and boundary of cytoplasm and nucleus. Canny detector algorithm was preferred and applied to a cervical cell images with the value of sensitivity of 0.634 and value of sigma was 6.56. We obtained the gradient images with smooth edges and boundary of cytoplasm and nucleus. Otsus algorithm was used to separate cytoplasm from the background. Maximum gray gradient difference (MGLGD) method adopted to extract nucleus contour. The results shows that segmentation gives impressive performance which will help further steps of automatic screening and detection of cervical cancer from Pap smear cervical cells image.
Other Latest Articles
- Overall Review of Vocabulary of Nakhchivan Dialect
- Water Quality Analysis in Sanaswadi, Pune
- Strategic Factors Influencing the Growth of Small and Medium Enterprises in the Central Business District of Mombasa County
- An Alternative Source of Livelihood: Socio-Economic Analysis of Organic Vegetable Growing in Nepal: A Case Study
- A Study of Audio Captcha and their Limitations
Last modified: 2021-06-30 21:44:39