Stochastic-offset-strategy enhanced RF pulse optimization with auto-differentiation

Motivation: Voxel-wise objective function with auto-differentiation for RF pulse optimization has become prevalent. While benefit from the spatial flexibility of desired pattern, conventional fixed-point representation of a matrix fed into the voxel-wise objective function leads to sub-optimal and undesired resultant profile at courser resolution. Goal(s): This abstract aims to address the issues of fixed-point artifact in the resultant excitation/refocusing profile. Approach: We proposed a method called stochastic-offset-approach which assigns random spatial offsets to each point centered at voxel. The objective function is evaluated on this modified set of points. Results: The results show that our proposed method achieve superior performance compared with fixed-point method. Impact: This method would significantly speed up and improve the performance of optimizations with voxel-wise objective function evaluated at fixed points under coarser resolution.