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Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Image Processing and Machine Learning Techniques for the Segmentation of cDNA Microarray Images

Image Processing and Machine Learning Techniques for the Segmentation of cDNA Microarray Images
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Author(s): Nikolaos Giannakeas (University of Ioannina, Greece)and Dimitrios I. Fotiadis (University of Ioannina, Greece)
Copyright: 2012
Pages: 13
Source title: Machine Learning: Concepts, Methodologies, Tools and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-60960-818-7.ch406

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Abstract

Microarray technology allows the comprehensive measurement of the expression level of many genes simultaneously on a common substrate. Typical applications of microarrays include the quantification of expression profiles of a system under different experimental conditions, or expression profile comparisons of two systems for one or more conditions. Microarray image analysis is a crucial step in the analysis of microarray data. In this chapter an extensive overview of the segmentation of the microarray image is presented. Methods already presented in the literature are classified into two main categories:methods which are based on image processing techniques and those which are based on Machine learning techniques. A novel classification-based application for the segmentation is also presented to demonstrate efficiency.

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