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

页码：110 / 113

页数：4

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