• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Automatic Sputum Color Image Segmentation for Lung Cancer Diagnosis

Vol. 7, No.1, January 30,2013
10.3837/tiis.2013.01.005, Download Paper (Free):

Abstract

Lung cancer is considered to be the leading cause of cancer death worldwide. A technique commonly used consists of analyzing sputum images for detecting lung cancer cells. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid errors. The manual screening of sputum samples has to be improved by using image processing techniques. In this paper we present a Computer Aided Diagnosis (CAD) system for early detection and diagnosis of lung cancer based on the analysis of the sputum color image with the aim to attain a high accuracy rate and to reduce the time consumed to analyze such sputum samples. In order to form general diagnostic rules, we present a framework for segmentation and extraction of sputum cells in sputum images using respectively, a Bayesian classification method followed by region detection and feature extraction techniques to determine the shape of the nuclei inside the sputum cells. The final results will be used for a (CAD) system for early detection of lung cancer. We analyzed the performance of a Bayesian classification with respect to the color space representation and quantification. Our methods were validated via a series of experimentation conducted with a data set of 100 images. Our evaluation criteria were based on sensitivity, specificity and accuracy.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
Fatma Taher, Naoufel Werghi and Hussain Al-Ahmad, "Automatic Sputum Color Image Segmentation for Lung Cancer Diagnosis," KSII Transactions on Internet and Information Systems, vol. 7, no. 1, pp. 68-80, 2013. DOI: 10.3837/tiis.2013.01.005

[ACM Style]
Taher, F., Werghi, N., and Al-Ahmad, H. 2013. Automatic Sputum Color Image Segmentation for Lung Cancer Diagnosis. KSII Transactions on Internet and Information Systems, 7, 1, (2013), 68-80. DOI: 10.3837/tiis.2013.01.005