The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Image Processing and Machine Learning Techniques for the Segmentation of cDNA
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.
Related Content
|
Julia Zimmer, Elisa Degenkolbe, Britt Wildemann, Petra Seemann.
© 2013.
30 pages.
|
|
George I. Lambrou, Maria Adamaki, Apostolos Zaravinos.
© 2013.
22 pages.
|
|
Svetoslav Nikolov, Mukhtar Ullah, Momchil Nenov, Julio Vera Gonzalez, Peter Raasch, Olaf Wolkenhauer.
© 2013.
23 pages.
|
|
Ana M. Sotoca, Michael Weber, Everardus J. J. van Zoelen.
© 2013.
19 pages.
|
|
Franz Ricklefs, Sonja Schrepfer.
© 2013.
16 pages.
|
|
Sonja Schallenberg, Cathleen Petzold, Julia Riewaldt, Karsten Kretschmer.
© 2013.
25 pages.
|
|
Ali Mobasheri.
© 2013.
32 pages.
|
|
|