Improved Fast Whole-Brain High Resolution Diffusion Imaging on 7 Tesla MRI

Achieving high resolution in diffusion MRI is challenging due to its inherently low SNR, vulnerability to motion and other EPI-related artifacts. On higher field-strengths, the SNR advantage can be exploited to push the resolution if the echo-time can be effectively reduced and the increased number of slices can be efficiently acquired. Combining acceleration techniques such as multi-band and parallel imaging is critical for this approach. Here we combine two deep-learned reconstruction priors, one pertaining to the q-space and another pertaining to image artifact removal, into a model-based iterative reconstruction framework to improve the quality of highly accelerated high-resolution 7T DWIs.