MR reconstruction in k-space using Vision Transformer boosted with Masked Image Modeling

Masked image modeling (MIM) skim has recently been shown to pre-train vision transform (ViT) and works as an effective data augmentation. In this study, we proposed MR reconstruction algorithm using ViT with MIM in k-space. The proposed method showed better performance than the original 1D and 2D ViT. Our study showed that MIM can be used to enhance the reconstruction quality to help learn the data distribution and that combining the loss in both k-space and spatial domain reconstructs images with better perceptuality.