Image registration is the process of finding a transformation that aligns one image to another. DIPY currently supports several numerical optimization-based techniques for image registration. Even though these methods perform well, they are limited by their slow registration speeds. The goal of this project is to develop deep-learning-based methods that can achieve image registration in one shot, resulting in much faster registration speeds. In this project, I propose to develop several deep neural networks for affine and deformable MRI registration. Additionally, I also plan to implement thin-plate splines.