Convex Adam
Project description
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
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