Fuzzy Clustering Algorithms for cDNA Microarray Image Spots Segmentation

cDNA microarray image provides useful information about thousands of gene expressions simultaneously. Hence microarray image segmentation is an important task. In this paper, existing fuzzy clustering image segmentation methods in the literature have been tested for its suitability to perform segmentation of noisy cDNA microarray images. The algorithms considered for this purpose include fuzzy clustering based methods like, Fuzzy c-means (FCM), Possibilistic c means (PCM), Possibilistic fuzzy c means (PFCM) and Fuzzy local information c means (FLICM). The results of segmentation shows that FLICM is better in segmenting microarray spots compared to the other under the presence of noise.