A BaSiC tool for background and shading correction of optical microscopy images
Nature Communications2017Vol. 8(1), pp. 14836–14836
Citations Over TimeTop 1% of 2017 papers
Tingying Peng, Kurt S. Thorn, Timm Schroeder, Lichao Wang, Fabian J. Theis, Carsten Marr, Nassir Navab
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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