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BioVoxxel 3D Box

BioVoxxel 3D Box (bv3dbox)

Most of the known BioVoxxel Toolbox functions now for 2D and 3D images in one place. All functions are heavily based on GPU computing via the fabulous CLIJ2 library. Segmentation output is based stronger on labels (intensity coding of objects) instead of ROIs. Those labels can be equivalently used like ROIs with many CLIJ2 functions. Also label images created via other tools such as MorphoLibJ are suitable inputs for any plugin using labels.



GitHub GitHub release (latest by date including pre-releases)

Functionalities and Details

All functions are described in detail here: BioVoxxel 3D Box Github page


The BioVoxxel 3D Box are distributed via the BioVoxxel 3D Box (bv3dbox) update site


If you use this library and its functions to generate and publish results, please condider to acknowledge and cite the toolbox using the DOI.



GitHub issues

REMARK: This is currently still an early release and should be handled with care when creating results. Please inform me about any issues you encounter!


The BioVoxxel 3D Box funtions are heavily based and rely strongly on the CLIJ library family. Therefore, this development would have not been possible without the work of Robert Haase and colleagues.

Robert Haase, Loic Alain Royer, Peter Steinbach, Deborah Schmidt, Alexandr Dibrov, Uwe Schmidt, Martin Weigert, Nicola Maghelli, Pavel Tomancak, Florian Jug, Eugene W Myers. CLIJ: GPU-accelerated image processing for everyone. Nat Methods (2019)

J. Ollion, J. Cochennec, F. Loll, C. Escudé, T. Boudier. (2013) TANGO: A Generic Tool for High-throughput 3D Image Analysis for Studying Nuclear Organization. Bioinformatics 2013 Jul 15;29(14):1840-1.