Motion robust magnetic resonance imaging via efficient Fourier aggregation

Oren Solomon, Rémi Patriat, Henry Braun, Tara E. Palnitkar, Steen Moeller, Edward J. Auerbach, Kamil Ugurbil, Guillermo Sapiro, Noam Harel

Research output: Contribution to journalArticlepeer-review


We present a method for suppressing motion artifacts in anatomical magnetic resonance acquisitions. Our proposed technique, termed MOTOR-MRI, can recover and salvage images which are otherwise heavily corrupted by motion induced artifacts and blur which renders them unusable. Contrary to other techniques, MOTOR-MRI operates on the reconstructed images and not on k-space data. It relies on breaking the standard acquisition protocol into several shorter ones (while maintaining the same total acquisition time) and subsequent efficient aggregation in Fourier space of locally sharp and consistent information among them, producing a sharp and motion mitigated image. We demonstrate the efficacy of the technique on T2-weighted turbo spin echo magnetic resonance brain scans with severe motion corruption from both 3 T and 7 T scanners and show significant qualitative and quantitative improvement in image quality. MOTOR-MRI can operate independently, or in conjunction with additional motion correction methods.

Original languageEnglish
Article number102638
JournalMedical Image Analysis
StatePublished - Jan 2023
Externally publishedYes


  • Fourier aggregation
  • Image deblurring
  • Magnetic resonance imaging
  • Motion artifacts
  • Robust imaging


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