NDLI: An Automated Gridding and Segmentation Method for cDNA Microarray Image Analysis

Content Provider	IEEE Xplore Digital Library
Author	Wei-Bang Chen Chengcui Zhang Wen-Lin Liu
Copyright Year	2006
Description	Author affiliation: Dept. of Comput. & Inf. Sci., Alabama Univ., Birmingham, AL (Wei-Bang Chen; Chengcui Zhang)
Abstract	Gridding and spot segmentation are two critical steps in microarray gene expression data analysis. However, the problems of noise contamination and donut-shaped spots often make signal extraction process a labor intensive task. In this paper, we propose a three-step method for automatic gridding and spot segmentation. The method starts with a background removal and noise eliminating step, and then proceeds in two steps. The first step applies a fully unsupervised method to extract blocks and grids from the cleaned data. The second step applies a simple, progressive spot segmentation method to deal with inner holes and noise in spots. We tested its performance on real microarray images against a widely used software GenePix. Our results show that the proposed method deals effectively with poor-conditioned microarray images in both gridding and spot segmentation
Starting Page	893
Ending Page	898
File Size	937791
Page Count	6
File Format	PDF
ISBN	0769525171
ISSN	10637125
DOI	10.1109/CBMS.2006.37
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image analysis Data mining Gene expression Data analysis Contamination Signal processing Background noise Software testing Software performance
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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