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Microarray Image Pattern Analysis

Microarray images used to study gene expression in cancer diseases has recently attracted a variety of researchers including medical doctors, computational biologists, and bioinformaticians. Most commercial softwares rely heavily on manual operations to obtain spot features from a microarry image consisting of several hundreds to tens of thousdands of spots with the image resolution of 3000 pixels per inch or 1000 pixels per centimeter, which is not practical. We propose a nearly automatic approach for computing spot features and test our method by 30 cDNA microarray images made from the tissues of patients of gastric cancer provided by the angiogenesis research center at National Taiwan University (ARCNTU). The average of Pearson correlation coefficients between spot features obtained by our method and by Array-Pro Analyzer on 30 microarray images is over 0.92, which encourages our work.