An unsupervised artifact correction approach for the analysis of DNA microarray images | IEEE Conference Publication | IEEE Xplore

An unsupervised artifact correction approach for the analysis of DNA microarray images


Abstract:

Image processing for analysis of microarray images is an important and challenging problem because imperfections and fabrication artifacts often impair our ability to mea...Show More

Abstract:

Image processing for analysis of microarray images is an important and challenging problem because imperfections and fabrication artifacts often impair our ability to measure accurately the quantities of interest in these images. In this paper we propose a microarray image analysis framework that provides a new method that automatically addresses each spot area in the image. Then, a new unsupervised clustering method is used which is based on a Gaussian mixture model (GMM) and the minimum description length (MDL) criterion, that allows the automatic spot area segmentation and the image artifacts isolation and correction to obtain more accurate spot quantitative values. Experimental results demonstrates the advantages of the proposed scheme in efficiently analysing microarrays.
Date of Conference: 14-17 September 2003
Date Added to IEEE Xplore: 24 November 2003
Print ISBN:0-7803-7750-8
Print ISSN: 1522-4880
Conference Location: Barcelona, Spain

References

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