Jose EC Serralles1, Elfar Adalsteinsson2,3, Lawrence L Wald4, and Luca Daniel1
1Computational Prototyping Group (CPG), Research Laboratory of Electronics (RLE), Department of Electrical Engineering and Computer Science (EECS), Massachusetts Institute of Technology (MIT), Cambridge, MA, United States, 2Department of Electrical Engineering and Computer Science (EECS), Massachusetts Institute of Technology (MIT), Cambridge, MA, United States, 3Institute for Medical Engineering and Science (IMES), Massachusetts Institute of Technology (MIT), Cambridge, MA, United States, 4Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
1Computational Prototyping Group (CPG), Research Laboratory of Electronics (RLE), Department of Electrical Engineering and Computer Science (EECS), Massachusetts Institute of Technology (MIT), Cambridge, MA, United States, 2Department of Electrical Engineering and Computer Science (EECS), Massachusetts Institute of Technology (MIT), Cambridge, MA, United States, 3Institute for Medical Engineering and Science (IMES), Massachusetts Institute of Technology (MIT), Cambridge, MA, United States, 4Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
We present the continuation of our work on parametric coil optimization. In our work, we include the addition of global optimizers that yield better results and improve the reliability of the procedure. We verify these claims with a few numerical examples.
Experiment 1, with coils to the left and right. Figs. a and d show the initial and final setups, respectively. Figs. b and e show the initial and final transmit magnetic fields. Figs. c and f show the difference between the transmit fields and the desired fields.
A visual representation of the coil optimization procedure.