An automatic segmentation of cervical intraepithelial neoplasia (CIN3) from parabasal cells

Author

Aupayagoson, Chanyut

Author_Institution

Dept. of Comput. Eng., Rajamangala Univ. of Technol. Rattanakosin, Nakhonpathom, Thailand

fYear

2014

fDate

14-17 May 2014

Firstpage

1

Lastpage

4

Abstract

This paper presents a method to automatic segmentation of cervical intraepithelial neoplasia (CIN3) parabasal cervical cells from PAP Smear images. The proposed method based on the structural characteristics of cervical; the region of nucleus by using Active Contour Model (ACM). The energy function is minimized in order to correct the less gradient of image energy area; to correct the cloudy contour. The performance of the proposed method is evaluated by comparing the results from Linear Discriminant Analysis (LDA) to expert diagnosis. The experimental results performing with 100 normal cases and 100 abnormal cases shown classification rate 93.5%.

Keywords

cancer; cellular biophysics; gynaecology; image classification; image segmentation; medical image processing; minimisation; PAP smear image classification rate; PAP smear image segmentation; active contour model; automatic cervical intraepithelial neoplasia segmentation; energy function minimization; linear discriminant analysis; nucleus region; parabasal cervical cells; Active contours; Cancer; Educational institutions; Image segmentation; Lesions; Neoplasms; Noise; Active Contour model; Linear Discriminant Analysis; cervical intraepithelial neoplasia (CIN3); parabasal cervical cells;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2014 11th International Conference on

Conference_Location

Nakhon Ratchasima

Type

conf

DOI

10.1109/ECTICon.2014.6839788

Filename

6839788