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Abstract #4096

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

Molin Zhang1, Nicolas Arango1, Sebo Diaz2, Jacob White1, and Elfar Adalsteinsson1,2,3
1EECS, MIT, Cambridge, MA, United States, 2Harvard-MIT Health Sciences and Technology, MIT, cambridge, MA, United States, 3Institute for Medical Engineering and Science, MIT, Cambridge, MA, United States

Synopsis

Keywords: RF Pulse Design & Fields, RF Pulse Design & Fields

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.

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Keywords