Microarray image processing based on clustering and morphological analysis

Authors:
Shuanhu Wu;Hong Yan
Affiliations:
Department of Computer Engineering and Information Technology, City University of Hong Kong, Kowloon, Hong Kong, Tat Chee Avenue, Kowloon, HongKong;Department of Computer Engineering and Information Technology, City University of Hong Kong, Kowloon, Hong Kong, Tat Chee Avenue, Kowloon, HongKong and School of Electrical and Information Enginee ...
Venue:
APBC '03 Proceedings of the First Asia-Pacific bioinformatics conference on Bioinformatics 2003 - Volume 19
Year:
2003

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Abstract

Microarrays allow the monitoring of expressions for tens of thousands of genes simultaneously. Image analysis is an important aspect for microarray experiments that can affect subsequent analysis such as identification of differentially expressed genes. Image processing for microarray images includes three tasks: spot gridding, segmentation and information extraction. In this paper, we address the segmentation and information extraction problems, and proposed a new segmentation method based on K-means clustering and a new background and foreground correction algorithm based on mathematical morphological and histogram analysis for information extraction. The advantage of our method is that it does not have any restrictions for the shape of spots. We compare our experimental results with those obtained from the popular software GenePix.