convexAdam

Learn2Reg 2021 Submission

Fast and accurate optimisation for registration with little learning

Please see details in our paper and if you use the code, please cite the following: Siebert, H., Hansen, L., Heinrich, M.P. (2022). Fast 3D Registration with Accurate Optimisation and Little Learning for Learn2Reg 2021. In: Aubreville, M., Zimmerer, D., Heinrich, M. (eds) Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis. MICCAI 2021. Lecture Notes in Computer Science(), vol 13166. Springer, Cham. https://doi.org/10.1007/978-3-030-97281-3_25

and

Heinrich, M.P., Papież, B.W., Schnabel, J.A., Handels, H. (2014). Non-parametric Discrete Registration with Convex Optimisation. In: Ourselin, S., Modat, M. (eds) Biomedical Image Registration. WBIR 2014. Lecture Notes in Computer Science, vol 8545. Springer, Cham. https://doi.org/10.1007/978-3-319-08554-8_6

Excellent results on Learn2Reg 2021 challenge

• for multimodal CT/MR registration (Task1)
• intra-patient lung CT alignment (Task2)
• and inter-patient whole brain MRI deformations (Task3) Challenge Website