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Abstract #4490

Volumetric Reconstruction Resolves Off-Resonance Artifacts in Static and Dynamic PROPELLER MRI

Annesha Ghosh1, Gordon Wetzstein2, Mert Pilanci2, and Sara Fridovich-Keil2
1University of California, Berkeley, Berkeley, CA, United States, 2Stanford University, Stanford, CA, United States

Synopsis

Keywords: AI/ML Image Reconstruction, Motion Correction, Off-Resonance Correction, Video Reconstruction

Motivation: Off-resonance correction typically requires field map measurements or pretraining data, which are slow/difficult to collect.

Goal(s): We propose a physics-based strategy to address off-resonance artifacts using only PROPELLER measurements, by modeling an additional spectral dimension.

Approach: This strategy exploits an equivalence between measuring a PROPELLER blade at a certain angle, and viewing a relief sculpture at the same angle. In this equivalence, three-dimensional structures (fat) appear shifted along the blade/view direction relative to flatter structures (water).

Results: Our method resolves continuous chemical shift artifacts while allowing for video reconstruction of dynamic tissues. We provide preliminary results on synthetic static and dynamic data.

Impact: We use volumetric reconstruction to correct off-resonance artifacts and perform fat/water separation in PROPELLER MRI, without additional field map measurements or pretraining data. We hope our method opens the door to shorter scan times and higher temporal resolution imaging.

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Keywords