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Algorithms 2013, 6(3), 512-531; doi:10.3390/a6030512
Article

Extraction and Segmentation of Sputum Cells for Lung Cancer Early Diagnosis

1,* , 1
, 1
 and 2
Received: 12 November 2012; in revised form: 14 August 2013 / Accepted: 15 August 2013 / Published: 21 August 2013
(This article belongs to the Special Issue Machine Learning for Medical Imaging 2012)
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Abstract: Lung cancer has been the largest cause of cancer deaths worldwide with an overall 5-year survival rate of only 15%. Its symptoms can be found exclusively in advanced stages where the chances for patients to survive are very low, thus making the mortality rate the highest among all other types of cancer. The present work deals with the attempt to design computer-aided detection or diagnosis (CAD) systems for early detection of lung cancer based on the analysis of sputum color images. The aim is to reduce the false negative rate and to increase the true positive rate as much as possible. The early detection of lung cancer from sputum images is a challenging problem, due to both the structure of the cancer cells and the stained method which are employed in the formulation of the sputum cells. We present here a framework for the extraction and segmentation of sputum cells in sputum images using, respectively, a threshold classifier, a Bayesian classification and mean shift segmentation. Our methods are validated and compared with other competitive techniques via a series of experimentation conducted with a data set of 100 images. The extraction and segmentation results will be used as a base for a CAD system for early detection of lung cancer which will improve the chances of survival for the patient.
Keywords: lung cancer detection; image segmentation; sputum cells; threshold algorithm; bayesian classification; mean shift algorithm lung cancer detection; image segmentation; sputum cells; threshold algorithm; bayesian classification; mean shift algorithm
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Taher, F.; Werghi, N.; Al-Ahmad, H.; Donner, C. Extraction and Segmentation of Sputum Cells for Lung Cancer Early Diagnosis. Algorithms 2013, 6, 512-531.

AMA Style

Taher F, Werghi N, Al-Ahmad H, Donner C. Extraction and Segmentation of Sputum Cells for Lung Cancer Early Diagnosis. Algorithms. 2013; 6(3):512-531.

Chicago/Turabian Style

Taher, Fatma; Werghi, Naoufel; Al-Ahmad, Hussain; Donner, Christian. 2013. "Extraction and Segmentation of Sputum Cells for Lung Cancer Early Diagnosis." Algorithms 6, no. 3: 512-531.

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