Medical Image Computing and Computer Assisted Intervention – MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part III

In this work, we proposed a novel image-based MRI superresolution reconstruction (SRR) approach based on anisotropic acquisition schemes. We achieved superior reconstruction to state-of-the-art work by introducing a new multi-scale gradient field prior that guides the reconstruction of the high-resolution (HR) image. The prior improves both spatial smoothness and edge preservation. The inverse of the forward model of image formation is used to propagate the gradient guidance from the low-resolution (LR) images to the HR image space. The gradient fields over multiple scales were exploited for more accurate edge localization in the reconstruction. The proposed SRR allows inter-volume motion during the MRI scans and can incorporate with the LR images with arbitrary orientations and displacements in the frequency space, such as orthogonal and origin-shifted scans. The proposed approach was evaluated on the synthetic data as well as the data acquired on a Siemens 3T MRI scanner containing 45 MRI scans from 14 subjects. The evaluation results demonstrate that our proposed prior leads to improved SRR as compared to state-of-the-art priors, and that the proposed SRR obtains better results at lower or the same cost in scan time than direct HR acquisition. In particular, the anatomical structures of hippocampus can be clearly shown in our reconstructed images. This is a significant improvement for the in vivo studies of the hippocampus.