GPU-accelerated image processing in ImageJ using CLIJ

View the Project on GitHub clij/clij-docs

CLIJ: GPU-accelerated image processing for everyone


CLIJ is an OpenCL - ImageJ bridge and a Fiji plugin allowing users with entry-level skills in programming to build GPU-accelerated workflows to speed up their image processing. Increased efforts were put on documentation, code examples, interoperability, and extensibility. CLIJ is based on ClearCL, JOCL, Imglib2, ImageJ and SciJava.

If you use CLIJ, please cite it:

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 17, 5–6 (2020) doi:10.1038/s41592-019-0650-1

Older version in BioRxiv

If you search for support, please open a thread on the forum. forum



Development of CLIJ is a community effort. We would like to thank everybody who helped developing and testing. In particular thanks goes to Alex Herbert (University of Sussex), Bram van den Broek (Netherlands Cancer Institute), Brenton Cavanagh (RCSI), Brian Northan (True North Intelligent Algorithms), Bruno C. Vellutini (MPI CBG), Curtis Rueden (UW-Madison LOCI), Damir Krunic (DKFZ), Daniel J. White (GE), Gaby G. Martins (IGC), Guillaume Witz (Bern University), Siân Culley (LMCB MRC), Giovanni Cardone (MPI Biochem), Jan Brocher (Biovoxxel), Jean-Yves Tinevez (Institute Pasteur), Johannes Girstmair (MPI CBG), Juergen Gluch (Fraunhofer IKTS), Kota Miura, Laurent Thomas (Acquifer), Matthew Foley (University of Sydney), Matthias Arzt (MPI-CBG), Nico Stuurman (UCSF), Peter Haub, Pete Bankhead (University of Edinburgh), Pit Kludig, Pradeep Rajasekhar (Monash University), Ruth Whelan-Jeans, Tanner Fadero (UNC-Chapel Hill), Thomas Irmer (Zeiss), Tobias Pietzsch (MPI-CBG), Wilson Adams (VU Biophotonics)

R.H. was supported by the German Federal Ministry of Research and Education (BMBF) under the code 031L0044 (Sysbio II) and D.S. received support from the German Research Foundation (DFG) under the code JU3110/1-1. P.T. was supported by the European Regional Development Fund in the IT4Innovations national supercomputing center-path to exascale project, project number CZ.02.1.01/0.0/0.0/16_013/0001791 within the Operational Programme Research, Development and Education.