@inproceedings{33f123170cef4fb3adc96231a182aed4,
title = "Segmentation of sputum cell image for early lung cancer detection",
abstract = "Lung cancer has been the largest cause of cancer deaths worldwide with an overall 5-year survival rate of only 15%. Its early detection significantly increases the chances of an effective treatment. To that end, computer-aided diagnosis system using images of sputum stained smears has been an attractive approach due to its practicality, low cost, and invasiveness. In this context, we present a framework for the detection and segmentation of sputum cells in sputum images using respectively, a Bayesian classification and mean shift segmentation. Our methods are validated and compared with an other competitive technique via a series of experimentation conducted with a data set of 88 images.",
keywords = "Bayesian classification, cell detection, early lung cancer detection, mean shift, Medical image",
author = "N. Werghi and C. Donner and F. Taher and H. Alahmad",
year = "2012",
doi = "10.1049/cp.2012.0433",
language = "British English",
isbn = "9781849196321",
series = "IET Conference Publications",
number = "600 CP",
booktitle = "IET Conference on Image Processing, IPR 2012",
edition = "600 CP",
note = "IET Conference on Image Processing, IPR 2012 ; Conference date: 03-07-2012 Through 04-07-2012",
}
