Off-resonance artifacts in magnetic resonance imaging (MRI) are visual
distortions that occur when the actual resonant frequencies of spins within the
imaging volume differ from the expected frequencies used to encode spatial
information. These discrepancies can be caused by a variety of factors,
including magnetic field inhomogeneities, chemical shifts, or susceptibility
differences within the tissues. Such artifacts can manifest as blurring,
ghosting, or misregistration of the reconstructed image, and they often
compromise its diagnostic quality. We propose to resolve these artifacts by
lifting the 2D MRI reconstruction problem to 3D, introducing an additional
"spectral" dimension to model this off-resonance. Our approach is inspired by
recent progress in modeling radiance fields, and is capable of reconstructing
both static and dynamic MR images as well as separating fat and water, which is
of independent clinical interest. We demonstrate our approach in the context of
PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced
Reconstruction) MRI acquisitions, which are popular for their robustness to
motion artifacts. Our method operates in a few minutes on a single GPU, and to
our knowledge is the first to correct for chemical shift in gradient echo
PROPELLER MRI reconstruction without additional measurements or pretraining
data.

通过将 2D MRI 重建问题升级为 3D，引入额外的 “频谱” 维度来解决磁共振成像中的离谱伪影问题，并成功重建静态和动态 MR 图像以及分离脂肪和水，从而改善图像的诊断质量。