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

被引：2
|
作者：
Hu Yijun [1 ]
Weng Guirong [1 ]
机构：
[1] Soochow Univ, Sch Mech & Elect Engn, Suzhou, Peoples R China
来源：
2009 WASE INTERNATIONAL CONFERENCE ON INFORMATION ENGINEERING, ICIE 2009, VOL II | 2009年
关键词：
cDNA Microarray image; K-means clustering; Mathematical Morphology;
D O I：
10.1109/ICIE.2009.17
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：110 / 113
页数：4
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