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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics


  • Editor: Gregory W. Faris
  • Vol. 3, Iss. 10 — Sep. 22, 2008

Image analysis algorithms for cell contour recognition in budding yeast

Mats Kvarnström, Katarina Logg, Alfredo Diez, Kristofer Bodvard, and Mikael Käll  »View Author Affiliations

Optics Express, Vol. 16, Issue 17, pp. 12943-12957 (2008)

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Quantification of protein abundance and subcellular localization dynamics from fluorescence microscopy images is of high contemporary interest in cell and molecular biology. For large-scale studies of cell populations and for time-lapse studies, such quantitative analysis can not be performed effectively without some kind of automated image analysis tool. Here, we present fast algorithms for automatic cell contour recognition in bright field images, optimized to the model organism budding yeast (Saccharomyces cerevisiae). The cell contours can be used to effectively quantify cell morphology parameters as well as protein abundance and subcellular localization from overlaid fluorescence data.

© 2008 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(100.2960) Image processing : Image analysis
(110.0180) Imaging systems : Microscopy
(150.1135) Machine vision : Algorithms

ToC Category:
Image Processing

Original Manuscript: May 15, 2008
Revised Manuscript: July 2, 2008
Manuscript Accepted: July 24, 2008
Published: August 11, 2008

Virtual Issues
Vol. 3, Iss. 10 Virtual Journal for Biomedical Optics

Mats Kvarnström, Katarina Logg, Alfredo Diez, Kristofer Bodvard, and Mikael Käll, "Image analysis algorithms for cell contour recognition in budding yeast," Opt. Express 16, 12943-12957 (2008)

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