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

Tingying Peng, Kurt Thorn, Timm Schroeder, Lichao Wang, Fabian J. Theis, Carsten Marr () and Nassir Navab ()
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Tingying Peng: Chair of Computer Aided Medical Procedure, Technische Universität München
Kurt Thorn: University of California, San Francisco, 600 16th Street, San Francisco, California 94158, USA
Timm Schroeder: ETH Zurich
Lichao Wang: Chair of Computer Aided Medical Procedure, Technische Universität München
Fabian J. Theis: Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health, Institute of Computational Biology
Carsten Marr: Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health, Institute of Computational Biology
Nassir Navab: Chair of Computer Aided Medical Procedure, Technische Universität München

Nature Communications, 2017, vol. 8, issue 1, 1-7

Abstract: 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.

Date: 2017
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DOI: 10.1038/ncomms14836

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