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CloudReg: automatic terabyte-scale cross-modal brain volume registration

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Fig. 1: CloudReg.

Data availability

The datasets in this study are available from the corresponding author on reasonable request.

Code availability

The CloudReg pipeline is open-source and available under an Apache 2.0 license at and at (ref. 11).


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This work was supported by R01 AG066184/AG/NIA NIH HHS/United States and by the National Science Foundation (NSF) under NSF Award Number EEC-1707298. The authors would also like to thank Microsoft Research for supporting this work. V.C. was supported by UPENN/NIH grant 133284. D.J.T. was supported by the Kavli Neuroscience Discovery Institute, the Karen Toffler Charitable Trust through the Toffler Scholar Program, and the NIH (U19MH114821). A.K.C. was supported by DARPA grant W911NF-14-2-0013 and NIMH TR01 R01 MH099647. M.A.W. was supported by NIDDK grant K08MH113039, DARPA grant W911NF-14-2-0013 and NIMH TR01 R01 MH099647. B.Y.H. was supported by DARPA grant W911NF-14-2-0013 and NIMH TR01 R01 MH099647. F.G. was supported by NARSAD Young Investigator Award from BBRF, K99 from NIDA (1K99DA050662-01), DARPA grant W911NF-14-2-0013 and NIMH TR01 R01 MH099647. T.A.M. was supported by the AP Giannini Foundation, a Stanford Dean’s Fellowship, NIH/NINDS (K99-NS116122), DARPA grant W911NF-14-2-0013 and NIMH TR01 R01 MH099647. A.B. was supported by National Institute of Health (NIH) (grant P01AG009973 and the Johns Hopkins University Kavli Neuroscience Discovery Institute Postdoctoral Fellowship. J.S.R. was supported in part by the intramural program of the NCI at the NIH. K.D. was supported by DARPA grant W911NF-14-2-0013 and NIMH TR01 R01 MH099647. J.T.V. was supported by R01 AG066184/AG/NIA NIH HHS/United States, EEC-1707298, UPENN/NIH grant 133284 and Microsoft Research.

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Authors and Affiliations



V.C. conceived the study, drafted the original manuscript, performed data analysis, built a reproducible pipeline and revised the manuscript. D.J.T. conceived the study, revised the manuscript, performed data analysis and supervised data analysis. D.C. ported registration algorithm to Python, performed data analysis and revised the manuscript. A.K.C., M.A.W., B.Y.H., F.G., T.A.M. and A.B. provided CLARITY/iDISCO/SHIELD LSM data and revised the manuscript. J.S.R. helped draft the original manuscript, revised the manuscript, provided data and placed landmarks for determining registration accuracy. K.D. and J.T.V. conceived the study, supervised data analysis and revised the manuscript.

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Correspondence to Joshua T. Vogelstein.

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The authors declare no competing interests.

Supplementary information

Supplementary Information

Supplementary Note, Figures 1–5 and References

Video 1

The progression of our registration over 5,000 iterations is shown. Our input LSM-imaged CLARITY mouse brain is shown in magenta and the ARA is shown in green. The overlap between the input data and the atlas is shown in grayscale. LSM, light-sheet microscopy; CLARITY, clear lipid-exchanged anatomically rigid imaging/immunostaining-compatible tissue hydrogel; ARA, Allen Reference Atlas.

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Chandrashekhar, V., Tward, D.J., Crowley, D. et al. CloudReg: automatic terabyte-scale cross-modal brain volume registration. Nat Methods 18, 845–846 (2021).

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