Segmentation of cDNA Microarray Spots Using K-means Clustering Algorithm and Mathematical Morphology

Complementary DNA microarray technology is a powerful tool in many areas. Usually a two channel microarray Red Green (RC) image is obtained. Due to the nature of cDNA microarray technology, a number of impairments affect the cDNA microarray image before the analysis such as identification of differentially expressed genes. Microarray image processing plays a crucial role in the extraction and quantitative analysis of the relative abundance of the DNA product. In this paper, a method combined K-means clustering algorithm and mathematical morphology is presented. Mathematical morphology is a useful tool for extracting image components. K-means clustering algorithm has a good performance in the segmentation of microarray image processing. The result of the experiment shows that the method presented in this paper is accurate, automatic and robust.