Keywords: Hybrid & Novel Systems Technology, Simulations, spatial encoding
Motivation: Design of accessible scanners may require accounting for substantial magnetic field inhomogeneities, which challenge assumptions used in MRI simulators.
Goal(s): To capture the encoding effects of strong field variations accurately and efficiently, predicting distortions of input images.
Approach: We discretized magnetic fields as usual but extended the MR signal simulation at each grid point from the 0th-order approximation, which assumes a locally-constant field, to a 1st-order approximation, which assumes a locally-linear field.
Results: The 1st-order approximation, which has an analytic solution, better captures strongly varying fields and enables simulations on a coarser grid, greatly improving computational efficiency.
Impact: The simulator enables evaluation of scanner designs with strongly varying magnetic fields. Simulated images can be utilized to generate training data efficiently from existing ground-truth images, enabling exploration of machine-learning techniques prior to the construction of prototype systems.
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