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An Automated Gridding and Segmentation Method for cDNA Microarray Image Analysis

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3 Author(s)
Wei-Bang Chen ; Dept. of Comput. & Inf. Sci., Alabama Univ., Birmingham, AL ; Chengcui Zhang ; Wen-Lin Liu

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

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Computer-Based Medical Systems, 2006. CBMS 2006. 19th IEEE International Symposium on

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