A Hill-Climbing Approach for Automatic Gridding of cDNA Microarray Images
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Sub-grid detection in DNA microarray images
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Constructing the histogram representation for automatic gridding of cDNA microarray images
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Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
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The paper reports a novel approach for the problem of automatic gridding in Microarray images. The solution is modeled as a Bayesian Random Field with a Gibbs prior possibly containing first order cliques (1-clique). On the contrary of previously published contributions, this paper does not assume second order cliques, instead it relies on a two step procedure to locate microarray spots. First a set of guide spots are used to interpolate a reference grid. The final grid is then produced by an a-posteriori maximization which takes into account the reference rectangular grid and local deformations. The algorithm is completely automatic and no human intervention is required, the only critical parameter being the range of the radius of the guide spots.