@inproceedings{7532b722a72d459dba6940061669434b,
title = "Segmentation of abnormal cells by using level set model",
abstract = "Segmentation of image is used from a long time in medical image applications and its study is increased for enhanced the medical diagnosis. This paper concerns a deformable segmentation method for abnormal cells detection by using an improved Level set model which is solved several problems and disadvantages of others segmentation technique. Our approach employed by using real data of carcinoma cells obtained from optical microscopy. Preliminary simulation results showed high performance metrics of the proposed model. Comparative study with manual segmentation demonstrated and confirmed that the level set can be a promise model of abnormal cells detection and in a particularly an irregular shape like carcinoma cells type.",
keywords = "Carcinoma, Level-set, Microscopy, Segmentation",
author = "Hawraa Haj-Hassan and Ahmad Chaddad and Camel Tanougast and Youssef Harkouss",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014 ; Conference date: 03-11-2014 Through 05-11-2014",
year = "2014",
month = dec,
day = "23",
doi = "10.1109/CoDIT.2014.6996994",
language = "English (US)",
series = "Proceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "770--773",
editor = "Imed Kacem and Pierre Laroche and Zsuzsanna Roka",
booktitle = "Proceedings - 2014 International Conference on Control, Decision and Information Technologies, CoDIT 2014",
}