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An active-contour based algorithm for the automated segmentation of dense yeast populations on transmission microscopy images

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Computing and Visualization in Science

Abstract

An image-processing pipeline for the automated segmentation of yeast cells in microscopy images is proposed. The method is suitable for the non-invasive detection of individual cells in transmission data which can be acquired simultaneously with fluorescence data. It moreover takes the varying quality and highly heterogeneous characteristics of cells in transmission images into account, is capable to process images with dense yeast populations and can be used to extract quantitative cell-based data from transmission/fluorescence image pairs. Applicability and performance of the method is evaluated on a data set of 523 different yeast deletion mutant strains.

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Authors and Affiliations

  1. Institute of Mathematics and Scientific Computing, University of Graz, Heinrichstraße 36/III, 8010, Graz, Austria

    Kristian Bredies

  2. Institute of Molecular Biosciences, Department of Biochemistry, University of Graz, Humboldtstraße 50/II, 8010, Graz, Austria

    Heimo Wolinski

Authors
  1. Kristian Bredies
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  2. Heimo Wolinski
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Correspondence to Kristian Bredies.

Additional information

Kristian Bredies acknowledges support by the Austrian Science Fund (FWF) special research grant SFB F32 “Mathematical Optimization and Applications in Biomedical Sciences”. This work was supported by grants from the Austrian Science Funds, FWF, project [F3005-B12 LIPOTOX] and the Federal Ministry of Science and Research [Project GOLD - Genomics of lipid-associated disorders, in the framework of the Austrian Genome program, GEN-AU], to Heimo Wolinski.

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Bredies, K., Wolinski, H. An active-contour based algorithm for the automated segmentation of dense yeast populations on transmission microscopy images. Comput. Visual Sci. 14, 341–352 (2011). https://doi.org/10.1007/s00791-012-0178-8

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  • DOI: https://doi.org/10.1007/s00791-012-0178-8

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