Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images

@article{Casamitjana2021SynthbyRegC,
  title={Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images},
  author={Adri{\`a} Casamitjana and Matteo Mancini and Juan Eugenio Iglesias},
  journal={Simulation and synthesis in medical imaging : ... International Workshop, SASHIMI ..., held in conjunction with MICCAI ..., proceedings. SASHIMI},
  year={2021},
  volume={12965},
  pages={
          44-54
        }
}
  • A. Casamitjana, M. Mancini, J. E. Iglesias
  • Published 30 July 2021
  • Medicine, Computer Science, Engineering
  • Simulation and synthesis in medical imaging : ... International Workshop, SASHIMI ..., held in conjunction with MICCAI ..., proceedings. SASHIMI
Nonlinear inter-modality registration is often challenging due to the lack of objective functions that are good proxies for alignment. Here we propose a synthesis-by-registration method to convert this problem into an easier intra-modality task. We introduce a registration loss for weakly supervised image translation between domains that does not require perfectly aligned training data. This loss capitalises on a registration U-Net with frozen weights, to drive a synthesis CNN towards the… 

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