SynthMorph: Learning Contrast-Invariant Registration Without Acquired Images

@article{Hoffmann2022SynthMorphLC,
  title={SynthMorph: Learning Contrast-Invariant Registration Without Acquired Images},
  author={Malte Hoffmann and Benjamin Billot and Douglas N. Greve and Juan Eugenio Iglesias and Bruce R. Fischl and Adrian V. Dalca},
  journal={IEEE transactions on medical imaging},
  year={2022},
  volume={41},
  pages={543 - 558}
}
We introduce a strategy for learning image registration without acquired imaging data, producing powerful networks agnostic to contrast introduced by magnetic resonance imaging (MRI). While classical registration methods accurately estimate the spatial correspondence between images, they solve an optimization problem for every new image pair. Learning-based techniques are fast at test time but limited to registering images with contrasts and geometric content similar to those seen during… 
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