@inproceedings{2b50fc5109cb4d709dd946b7ae6728b9,
title = "Detection and segmentation of sputum cell 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. For this purpose, a computer-aided design system using images of sputum stained smears is a practical, low-cost, and totally non invasive solution. In this paper, 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 other competitive approaches via a series of experiments conducted with a data set of 88 images.",
keywords = "Bayesian classification, cell detection, early lung cancer detection, mean shift, medical image",
author = "Naoufel Werghi and Christian Donner and Fatma Taher and Hussain Al-Ahmad",
year = "2012",
doi = "10.1109/ICIP.2012.6467484",
language = "British English",
isbn = "9781467325332",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "2813--2816",
booktitle = "2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings",
note = "2012 19th IEEE International Conference on Image Processing, ICIP 2012 ; Conference date: 30-09-2012 Through 03-10-2012",
}
