Jian Zhang1,2, Daniel Rettmann3, Eric Han4, Cooper Roddey5, Nate White5, Joshua Kuperman5, Juan Santos1, Anders Dale5,6, Ajit Shankaranarayanan4
1Department of Electrical Engineering, Stanford University, Stanford, CA, USA; 2Department of Radiology, Stanford University, Stanford, CA, USA; 3Global Applied Science Lab, GE Healthcare, Rochester, MN, USA; 4Global Applied Science Lab, GE Healthcare, Menlo Park, CA, USA; 5Department of Neuroscience, University of California, San Diego, La Jolla, CA, USA; 6Department of Radiology, University of California, San Diego, La Jolla, CA, USA
In this work, quantitative off-line evaluations have been performed to study the accuracy and stability of PROMO. With the aid of our off-line PROMO simulation package, various impacting factors, including navigator prescription parameters, navigator reconstruction filters, image noises, and motion patterns, have been studied. An optimal PROMO parameter configuration has been proposed. And both simulation and in vivo results show that this optimization improves the algorithm performance significantly. Furthermore, since our offline system contains independent coordinate translation and gradient adjustment simulation module, it can be easily applied to evaluate other motion correction algorithms as well.
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