Joint Retrospective Motion Correction and Reconstruction for Brain MRI With a Reference Contrast

Publication date

2022

Authors

Rizzuti, Gabrio
Sbrizzi, AlessandroORCID 0000-0003-3276-4542ISNI 0000000396833383
Van Leeuwen, Tristan

Editors

Advisors

Supervisors

Document Type

Article

Collections

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License

taverne

Abstract

We present a retrospective joint motion correction and reconstruction scheme for magnetic resonance imaging to reduce the imprint of subject motion on the reconstructed images. In multi-contrast imaging, reconstructions pertaining to distinct acquisition sequences (e.g., T1 or T2 weighted images) might not be equally affected by motion, due to the sequential nature of the data acquisition process or the specific sequence design. To avoid repeating the corrupted scan, we can leverage the uncorrupted reconstructions to post-process the contrasts that are most severely affected by motion, by assuming a shared underlying anatomy. Only rigid motion is considered here, but no further assumptions are required. Classical motion correction schemes are combined with weighted total-variation regularization, whose weight is defined by the structure of the well-resolved contrasts. We will particularly focus on brain imaging with conventional Cartesian sampling. We envision a practical workflow that can easily fit into the existing clinical practice without the need for changing the MRI acquisition protocols.

Keywords

compressed sensing, Magnetic resonance imaging, motion correction, structure-guided regularization, Taverne, Signal Processing, Computer Science Applications, Computational Mathematics

Citation

Rizzuti, G, Sbrizzi, A & Van Leeuwen, T 2022, 'Joint Retrospective Motion Correction and Reconstruction for Brain MRI With a Reference Contrast', IEEE Transactions on Computational Imaging, vol. 8, pp. 490-504. https://doi.org/10.1109/TCI.2022.3183383