recipe bioconductor-ebimage

Image processing and analysis toolbox for R







biotools: ebimage

EBImage provides general purpose functionality for image processing and analysis. In the context of (high-throughput) 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 facilitates the use of other tools in the R environment for signal processing, statistical modeling, machine learning and visualization with image data.

package bioconductor-ebimage

(downloads) docker_bioconductor-ebimage



depends bioconductor-biocgenerics:


depends bioconductor-biocgenerics:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-abind:

depends r-base:


depends r-fftwtools:


depends r-htmltools:

depends r-htmlwidgets:

depends r-jpeg:

depends r-locfit:

depends r-png:

depends r-rcurl:

depends r-tiff:



You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-ebimage

and update with::

   mamba update bioconductor-ebimage

To create a new environment, run:

mamba create --name myenvname bioconductor-ebimage

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-ebimage/tags`_ for valid values for ``<tag>``)

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