4.7 Article

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

Journal

IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
Volume 8, Issue -, Pages 490-504

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCI.2022.3183383

Keywords

Magnetic resonance imaging; motion correction; compressed sensing; structure-guided regularization

Funding

  1. Netherlands Organization for Health Research and Development (ZonMW) [104022007]

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The article presents a retrospective joint motion correction and reconstruction scheme to reduce the impact of subject motion on MRI images. The scheme leverages uncorrupted reconstructions to post-process contrasts most affected by motion, assuming a shared underlying anatomy. Rigid motion is considered, and classical motion correction schemes are combined with weighted total-variation regularization.
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., T-1 or T-2 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.

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