• 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