F3RNet: full-resolution residual registration network for deformable image registration.
Zhe XuJie LuoJiangpeng YanXiu LiJagadeesan JayenderPublished in: International journal of computer assisted radiology and surgery (2021)
By combining the high-resolution information and multi-scale representations in a highly interactive residual learning fashion, the proposed F3RNet can achieve accurate overall and local registration. The run time for registering a pair of images is less than 3 s using a GPU. In future works, we will investigate how to cost-effectively process high-resolution information and fuse multi-scale representations.