Literature DB >> 17945710

Extraction of the number of peroxisomes in yeast cells by automated image analysis.

Antti Niemistö1, Jyrki Selinummi, Ramsey Saleem, Ilya Shmulevich, John Aitchison, Olli Yli-Harja.   

Abstract

An automated image analysis method for extracting the number of peroxisomes in yeast cells is presented. Two images of the cell population are required for the method: a bright field microscope image from which the yeast cells are detected and the respective fluorescent image from which the number of peroxisomes in each cell is found. The segmentation of the cells is based on clustering the local mean-variance space. The watershed transformation is thereafter employed to separate cells that are clustered together. The peroxisomes are detected by thresholding the fluorescent image. The method is tested with several images of a budding yeast Saccharomyces cerevisiae population, and the results are compared with manually obtained results.

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Year:  2006        PMID: 17945710     DOI: 10.1109/IEMBS.2006.259890

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

1.  Genome-wide analysis of effectors of peroxisome biogenesis.

Authors:  Ramsey A Saleem; Rose Long-O'Donnell; David J Dilworth; Abraham M Armstrong; Arvind P Jamakhandi; Yakun Wan; Theo A Knijnenburg; Antti Niemistö; John Boyle; Richard A Rachubinski; Ilya Shmulevich; John D Aitchison
Journal:  PLoS One       Date:  2010-08-04       Impact factor: 3.240

2.  Efficient framework for automated classification of subcellular patterns in budding yeast.

Authors:  Seungil Huh; Donghun Lee; Robert F Murphy
Journal:  Cytometry A       Date:  2009-11       Impact factor: 4.355

3.  An algorithm to automate yeast segmentation and tracking.

Authors:  Andreas Doncic; Umut Eser; Oguzhan Atay; Jan M Skotheim
Journal:  PLoS One       Date:  2013-03-08       Impact factor: 3.240

  3 in total

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