 Critically, we show that input labels  need not be of actual anatomy: training on randomly synthesized shapes , or supervoxels, results in competitive registration performance and makes the network agnostic to anatomy and contrast, all while eradicating the need for real data .
<clarity>  Critically, we show that input labels  need not be of actual anatomy: training on randomly synthesized shapes , or supervoxels, results in competitive registration performance and makes the network agnostic to anatomy and contrast, all while eradicating the need for real data .
 Critically, we show that input labels need not be of actual anatomy: training on randomly generated geometric shapes also results in competitive registration performance and makes the network agnostic to anatomy and contrast, all while eradicating the need for real data .