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 (RG) 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.
cDNA Microarray image K-means clustering Mathematical Morphology
Hu Yijun Weng Guirong
School of Mechanic & Electronic Engineering Soochow University Suzhou, China
国际会议
2009 WASE International Conference on Information Engineering(2009年国际信息工程会议)(ICIE 2009)
太原
英文
769-772
2009-07-10（万方平台首次上网日期，不代表论文的发表时间）