Automated cDNA microarray image segmentation

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Author(s)
Liew, Alan Wee-Chung
Yan, Hong
Griffith University Author(s)
Year published
2007
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Show full item recordAbstract
cDNA microarray technology enables whole genome study of gene expressions by measuring the differential expression of genes in microarray images. An important first step in analyzing microarray image is the accurate delineation of the cDNA spots in the image. We report here a fully automated spot segmentation algorithm for cDNA microarray images. The algorithm makes use of morphological operations, adaptive multi-level thresholding, and statistical intensity modeling to perform automatic grid addressing and spot segmentation. Our algorithm is robust for even poor quality cDNA microarray images.cDNA microarray technology enables whole genome study of gene expressions by measuring the differential expression of genes in microarray images. An important first step in analyzing microarray image is the accurate delineation of the cDNA spots in the image. We report here a fully automated spot segmentation algorithm for cDNA microarray images. The algorithm makes use of morphological operations, adaptive multi-level thresholding, and statistical intensity modeling to perform automatic grid addressing and spot segmentation. Our algorithm is robust for even poor quality cDNA microarray images.
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Conference Title
COMPUTATIONAL MODELS FOR LIFE SCIENCES (CMLS 07)
Volume
952
Publisher URI
Copyright Statement
© 2007 American Institute of Physics. The attached file is reproduced here in accordance with the copyright policy of the publisher. Use hypertext link for access to the conference website.