DocumentCode
2817922
Title
Microarray Image Processing Using Expectation Maximization Algorithm and Mathematical Morphology
Author
Guirong, Weng ; Jian, Su
Author_Institution
Sch. of Mechanic & Electron. Eng., Soochow Univ., Suzhou, China
Volume
1
fYear
2009
fDate
24-26 April 2009
Firstpage
577
Lastpage
579
Abstract
Image processing is an important aspect of microarray experiments. Spots segmentation, which is to distinguish the spot signals from background pixels, is a critical step in microarray image processing. After analyzing other means of microarray segmentation, a new method based on expectation maximization (EM) algorithm, mathematical morphological filtering and morphological processing is presented. And its corresponding theory and realizable steps are introduced in this paper. Simulations show that the new method for spot image segmentation has better performance than most common ways, such as the ScanAlizeTM method and GenePixTM method. The results of experiments, which are computationally attractive, have excellent performance and can preserve structural information while efficiently suppressing noise in DNA microarray data.
Keywords
bioinformatics; expectation-maximisation algorithm; filtering theory; image denoising; image segmentation; lab-on-a-chip; mathematical morphology; DNA microarray data; GenePixTM method; ScanAlizeTM method; background pixel; expectation maximization algorithm; image processing; mathematical morphological filtering; noise suppression; spot image segmentation; Filtering algorithms; Genetics; Image processing; Image segmentation; Iterative algorithms; Morphology; Pixel; Probes; Signal processing; Visualization; EM Algorithm; Image Segmentation; cDNA Microarray Image; morphological operator;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location
Sanya, Hainan
Print_ISBN
978-0-7695-3605-7
Type
conf
DOI
10.1109/CSO.2009.91
Filename
5193762
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