Publication Type : Journal Article
Publisher : 2, Issue 3,
Source : 2, Issue 3, p.147 – 158 (2012)
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Verified : Yes
Year : 2012
Abstract : Early detection of lung cancer is a challenging problem, the world faces today. Prior to classify glandular cells as malignant or benign a reliable segmentation technique is required. In this paper we present a novel lung glandular cell segmentation technique. The technique uses a combination of multiple color spaces andvarious clustering algorithms to automatically find the best possible segmentation result. Unsupervised clustering methods of K-means and Fuzzy C-means were used on multiple color spaces such as HSV, LAB, LUV, xyY. Experimental results of segmentation using various color spaces are provided to show theperformance of the proposed system.
Cite this Research Publication : S. S Kecheril, Dr. Venkataraman D., Suganthi, J., and Sujathan, K., “Segmentation of lung glandular cells using multiple color spaces”, 2, no. 3, pp. 147 – 158, 2012.