CLIJ: GPU-accelerated image processing for everyone

Article metrics

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: CLIJ performance overview.

Data availability

All data to support our findings are available through the links listed in Supplementary Table 2. Further details can be found in the Reporting Summary.

Code availability

CLIJ is available as Supplementary Software 2. The fully open source code is available through the links listed in Supplementary Table 2. Updated versions of the software can also be found at https://clij.github.io. Further details can be found in the Reporting Summary.

References

  1. 1.

    Preibisch, S. et al. Nat. Methods 11, 645–648 (2014).

  2. 2.

    Laine, R. F. et al. J. Phys. Appl. Phys. 52, 163001 (2019).

  3. 3.

    Culley, S. et al. Nat. Methods 15, 263–266 (2018).

  4. 4.

    Weigert, M. et al. Nat. Methods 15, 1090–1097 (2018).

  5. 5.

    Falk, T. et al. Nat. Methods 16, 67–70 (2019).

  6. 6.

    Schmid, B. et al. Nat. Methods 16, 278–280 (2019).

  7. 7.

    Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. Nat. Methods 9, 671–675 (2012).

  8. 8.

    Schindelin, J. et al. Nat. Methods 9, 676–682 (2012).

  9. 9.

    The Khronos Group. The open standard for parallel programming of heterogeneous systems https://www.khronos.org/opencl/ (2019).

  10. 10.

    Rueden, C. T. et al. BMC Bioinform. 18, 529 (2017).

Download references

Acknowledgements

We would like to thank everybody who helped developing and testing CLIJ. In particular thanks goes to A. Herbert (University of Sussex), B. C. Vellutini (MPI-CBG), C. Rueden (UW-Madison LOCI), D. Krunic (DKFZ), D. J. White (GE), G. G. Martins (IGC), S. Culley (LMCB MRC), G. Cardone (MPI Biochem), J. Brocher (Biovoxxel), J. Girstmair (MPI-CBG), J. Gluch (Fraunhofer IKTS), K. Miura, L. Thomas (Acquifer), N. Stuurman (UCSF), P. Haub, P. Rajasekhar (Monash University), T. Pietzsch (MPI-CBG), W. 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.

Author information

R.H. and L.A.R initiated the research. R.H., L.A.R., P.S, D.S., A.D., U.S. and M.W. wrote the source code of CLIJ. R.H. and N.M. performed the image acquisition of the example data. E.W.M. supervised the project. R.H., L.A.R., U.S., M.W., P.T. and F.J. wrote the manuscript with input from all co-authors.

Correspondence to Robert Haase or Loic A. Royer.

Ethics declarations

Competing interests

The authors declare no competing interests.

Supplementary information

Supplementary Information

Supplementary Figures 1–7, Supplementary Tables 1 and 2, and Supplementary Notes 1 and 2.

Reporting Summary

Supplementary Video 1

Results from processed time-lapse for benchmarking workflow. A video showing a developing Drosophila embryo in maximum projection and cylinder maximum projection with marked spot detection and spot count plotted over time.

Supplementary Software 1

CLIJ usage examples: Scripts demonstrating CLIJ in various ImageJ/Fiji compatible programming languages.

Supplementary Software 2

Reviewed version of CLIJ software.

Source data

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Haase, R., Royer, L.A., Steinbach, P. et al. CLIJ: GPU-accelerated image processing for everyone. Nat Methods (2019) doi:10.1038/s41592-019-0650-1

Download citation