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cDNA microarray image segmentation using root signals
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DOI：10.1002/ima.20067.png)
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Abstract
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A vector processing based framework suitable for cDNA microarray image segmentation is introduced and analyzed in this paper. By using nonlinear, generalized selection vector filters the framework proposed here classifies the cDNA image data as either microarray spots or image background. The solution converges to a root signal that represents the segmented cDNA microarray image with the regular spots ideally separated from the background and with their coloration uniquely described by dominant color vectors. It will be demonstrated that the framework readily unifies image denoising, enhancement, data normalization, irregular spot rejection, and spot segmentation in one processing step delivering excellent performance at reasonable computational cost. (C) 2006 Wiley Periodicals, Inc.
Keywords:
cDNA microarray images
microarray analysis
image segmentation
vectorial approach
nonlinear image processing
filter design
root signals
convergence property
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