Review on image segmentation methods in cDNA microarray experiments and a novel algorithm for segmentation

Karun, Kalesh M and Binu, VS and Prasad, Keerthana and Nair, Sreekumaran N and Prasad, Manjunath K and Girisha, KM (2015) Review on image segmentation methods in cDNA microarray experiments and a novel algorithm for segmentation. International Journal of Emerging Science and Engineering (IJESE), 3 (5). pp. 23-24. ISSN 2319–6378

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Abstract

Microarray experiments are used to measure gene expression levels of thousands of genes at a time. The image analysis has an important role in the microarray data analysis and has potential impact on the identification of differentially expressed genes. Segmentation is one of the important processes in image analysis. The current paper attempts to provide an overview of commonly used segmentation methods in microarray image analysis like fixed circle segmentation, adaptive circle segmentation, the adaptive shape segmentation, histogram-based method and machine learning algorithms. We estimated intensity ratios of selected spots from an image file downloaded from the Gene Expression Omnibus (GEO) database based on the above segmentation methods. It was observed that all these methods give almost similar estimates of intensity ratio value. We are also proposing a new algorithm to identify the spot radius for the adaptive circle segmentation, instead of manual fixing of the radius.

Item Type: Article
Uncontrolled Keywords: Terms—Microarray; image analysis; segmentation; intensity ratio.
Subjects: Departments at MU > Statistics
Medicine > KMC Manipal > Paediatrics
Depositing User: KMC Manipal
Date Deposited: 28 Apr 2015 11:17
Last Modified: 28 Apr 2015 11:17
URI: http://eprints.manipal.edu/id/eprint/142564

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