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Nat Commun. 2017 Jun 8;8:14836. doi: 10.1038/ncomms14836.

A BaSiC tool for background and shading correction of optical microscopy images.

Author information

1
Department of Computer Science, Chair of Computer Aided Medical Procedure, Technische Universität München, Boltzmannstr. 3, Garching 85748, Germany.
2
Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, Institute of Computational Biology, Ingolstädter Landstraße 1, Neuherberg 85764, Germany.
3
Center for Mathematics, Chair of Mathematical Modeling of Biological Systems, Technische Universität München, Boltzmannstr. 3, Garching 85748, Germany.
4
Department of Biochemistry and Biophysics, University of California, San Francisco, 600 16th Street, San Francisco, California 94158, USA.
5
Department of Biosystems Science and Engineering (D-BSSE), ETH Zurich, Basel 4058, Switzerland.
6
Department of Computer Science, Chair of Computer Aided Medical Procedure, Johns Hopkins University, 3400 North Charles Street, Baltimore, Maryland 21218, USA.

Abstract

Quantitative analysis of bioimaging data is often skewed by both shading in space and background variation in time. We introduce BaSiC, an image correction method based on low-rank and sparse decomposition which solves both issues. In comparison to existing shading correction tools, BaSiC achieves high-accuracy with significantly fewer input images, works for diverse imaging conditions and is robust against artefacts. Moreover, it can correct temporal drift in time-lapse microscopy data and thus improve continuous single-cell quantification. BaSiC requires no manual parameter setting and is available as a Fiji/ImageJ plugin.

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