Before revision:  We build on a state-of-the-art learning-based registration method to improve the accuracy of sparse clinical image registration and demonstrate our method on a clinically-acquired MRI dataset of stroke patients . SparseVM registers 3D scans in under a second on a GPU, which is over 1000x faster than the most accurate clinical registration methods, without compromising accuracy. Because of this, SparseVM enables clinical analyses that were not previously possible. The code is publicly available at voxelmorph.mit.edu.
After revision:  We build on a state-of-the-art learning-based registration method to improve the accuracy of sparse clinical image registration and demonstrate our method on a clinically-acquired MRI dataset of stroke patients and on a simulated sparse MRI dataset. Our code is available as part of the VoxelMorph package at URL