Introduction

SuPReMo implements the unified motion modelling and image registration framework as proposed by Jamie McClelland et al. and was developed by Bjoern Eiben and the Radiotherapy Image Computing Group at the Centre for Medical Image Computing, University College London, UK. The publication describing the background of this software package in the context of a multi-slice image acquisition designed for an MR-Linac workflow can be found here.

The source code is available on github and the documentation is hosted on the corresponding github-pages.

If you publish any results using this package, please cite the following publications:

• Eiben, B., Bertholet, J., Tran, E.H., Wetscherek, A., Shiarli, A.M., Nill, S., Oelfke, U. and McClelland, J.R., 2024. Respiratory motion modelling for MR-guided lung cancer radiotherapy: model development and geometric accuracy evaluation. Physics in Medicine and Biology. doi: 10.1088/1361-6560/ad222f
• McClelland, J.R., Modat, M., Arridge, S., Grimes, H., D’Souza, D., Thomas, D., O’Connell, D., Low, D.A., Kaza, E., Collins, D.J. and Leach, M.O., 2017. A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images. Physics in Medicine & Biology, 62(11), p.4273. doi: 10.1088/1361-6560/aa6070

Related work:

• Huang, Y., Thielemans, K., Price, G. and McClelland, J.R., 2024. Surrogate-driven respiratory motion model for projection-resolved motion estimation and motion compensated cone-beam CT reconstruction from unsorted projection data. Physics in Medicine & Biology, 69(2), p.025020. doi: 10.1088/1361-6560/ad1546
• Tran, E.H., Eiben, B., Wetscherek, A., Oelfke, U., Meedt, G., Hawkes, D.J. and McClelland, J.R., 2020. Evaluation of MRI-derived surrogate signals to model respiratory motion. Biomedical physics & engineering express, 6(4), p.045015. doi: 10.1088/2057-1976/ab944c

Getting started

Below is a list of additional pages that will help you to get started with SuPReMo. These links will get you to the correspomding pages of the documentation.

• For information on how to build your own version and to get started with SuPReMo see getting started with SuPReMo.
• For an in-depth background see the background section.
• If you have used the previous implementation of the generalised framework called nifty-reg-resp, then you will find information on how to make the transition here.

Funding acknowledgements

The development of this software package was supported by Cancer Research UK under the Programme C33589/A19908, and a Cancer Research UK Centres Network Accelerator Award Grant (A21993) to the ART-NET Consortium.

License

This software is published under the BSD 3-Clause License as defined in the LICENSE.txt file of the source code and most importantly is distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.