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, 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. BioRxiv preprint. https://doi.org/10.1101/660704
If you search for support, please open a thread on the image.sc forum.
- CLIJ - a quick tour
- Installation
- Fiji update site
- Depending on CLIJ via maven
- Icy (experimental)
- ImageJ1 (experimental)
- Matlab (experimental)
- MicroManager 2.0 (experimental)
- Python (experimental)
- Introduction to CLIJ programming
- Application programming interface (API)
- Code examples
- Benchmarking
- Extending CLIJ functionality
- FAQ / support
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), Nico Stuurman (UCSF), Peter Haub, Pete Bankhead (University of Edinburgh), Pradeep Rajasekhar (Monash University), Tanner Fadero (UNC-Chapel Hill), Thomas Irmer (Zeiss), Tobias Pietzsch (MPI-CBG), Wilson Adams (VU Biophotonics)