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.
After revision:  We build on a state-of-the-art learning-based registration method , SparseVM, that is more accurate and orders of magnitude faster than the most accurate clinical registration methods. To our knowledge, it is the first method to use deep learning specifically tailored to registering clinical images. We 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.