DeepReg: a deep learning toolkit for medical image registration

Python Submitted 01 September 2020Published 04 November 2020

Editor: @Kevin-Mattheus-Moerman (all papers)
Reviewers: @ethanwharris (all reviews), @lbrea (all reviews), @zhangfanmark (all reviews)


Yunguan Fu (0000-0002-1184-7421), Nina Montaña Brown (0000-0001-5685-971X), Shaheer U. Saeed (0000-0002-5004-0663), Adrià Casamitjana (0000-0002-0539-3638), Zachary M. c. Baum (0000-0001-6838-335X), Rémi Delaunay (0000-0002-0398-4995), Qianye Yang (0000-0003-4401-5311), Alexander Grimwood (0000-0002-2608-2580), Zhe Min (0000-0002-8903-1561), Stefano B. Blumberg (0000-0002-7150-9918), Juan Eugenio Iglesias (0000-0001-7569-173X), Dean C. Barratt (0000-0003-2916-655X), Ester Bonmati (0000-0001-9217-5438), Daniel C. Alexander (0000-0003-2439-350X), Matthew J. Clarkson (0000-0002-5565-1252), Tom Vercauteren (0000-0003-1794-0456), Yipeng Hu (0000-0003-4902-0486)


Fu et al., (2020). DeepReg: a deep learning toolkit for medical image registration. Journal of Open Source Software, 5(55), 2705,

@article{Fu2020, doi = {10.21105/joss.02705}, url = {}, year = {2020}, publisher = {The Open Journal}, volume = {5}, number = {55}, pages = {2705}, author = {Yunguan Fu and Nina Montaña Brown and Shaheer U. Saeed and Adrià Casamitjana and Zachary M. c. Baum and Rémi Delaunay and Qianye Yang and Alexander Grimwood and Zhe Min and Stefano B. Blumberg and Juan Eugenio Iglesias and Dean C. Barratt and Ester Bonmati and Daniel C. Alexander and Matthew J. Clarkson and Tom Vercauteren and Yipeng Hu}, title = {DeepReg: a deep learning toolkit for medical image registration}, journal = {Journal of Open Source Software} }
Copy citation string · Copy BibTeX  

TensorFlow medical image registration image fusion deep learning neural networks

Markdown badge



Authors of JOSS papers retain copyright.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

Public user content licensed CC BY 4.0 unless otherwise specified.
ISSN 2475-9066