Clustering-based spot segmentation of cDNA microarray images

Microarrays are utilized as that they provide useful information about thousands of gene expressions simultaneously. In this study segmentation step of microarray image processing has been implemented. Clustering-based methods, fuzzy c-means and k-means, have been applied for the segmentation step t...

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Bibliographic Details
Published in:2010 Annual International Conference of the IEEE Engineering in Medicine and Biology 2010-01, p.1828-1831
Main Authors: Uslan, V, Bucak, İ Ö
Format: Article
Language:English
Subjects:
clustering
Clustering algorithms
Clustering methods
DNA
fuzzy c-means
Gene expression
Image segmentation
k-means
Microarray image segmentation
Pixel
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Summary:Microarrays are utilized as that they provide useful information about thousands of gene expressions simultaneously. In this study segmentation step of microarray image processing has been implemented. Clustering-based methods, fuzzy c-means and k-means, have been applied for the segmentation step that separates the spots from the background. The experiments show that fuzzy c-means have segmented spots of the microarray image more accurately than the k-means.
ISSN:1094-687X
1558-4615
DOI:10.1109/IEMBS.2010.5626430