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. 2010 Apr 1;26(7):979-81.
doi: 10.1093/bioinformatics/btq046.

EBImage--an R package for image processing with applications to cellular phenotypes

Grégoire Pau  1 , Florian Fuchs, Oleg Sklyar, Michael Boutros, Wolfgang Huber
Affiliations

EBImage--an R package for image processing with applications to cellular phenotypes

Grégoire Pau et al. Bioinformatics. .

Abstract

Summary: EBImage provides general purpose functionality for reading, writing, processing and analysis of images. Furthermore, in the context of microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and use of existing tools in the R environment for signal processing, statistical modeling, machine learning and data visualization.

Availability: EBImage is free and open source, released under the LGPL license and available from the Bioconductor project (http://www.bioconductor.org/packages/release/bioc/html/EBImage.html).

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Figures

Fig. 1.
Fig. 1.
From microscope images to cellular phenotypes. (a) Fluorescent microscopy images from three channels of the same population of HeLa cells perturbed by siRluc. (b) A false colour image combining the actin (red), the tubulin (green) and the DNA (blue) channels. (c) Nuclei boundaries (yellow) were segmented with adaptive thresholding followed by connected set labeling. (d) Cell membranes (magenta) were determined by Voronoi segmentation. (e) Distribution of the cell sizes compared to a population of HeLa cells perturbed by siCLSPN. Cells treated with siCLSPN were significantly enlarged compared to those perturbed with siRluc (Wilcoxon rank sum test, P<10−15).
See this image and copyright information in PMC

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