Publication Type:

Journal Article

Source:

2, Issue 3, p.147 – 158 (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 and
various 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 the
performance 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.

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