Vincent Gras1 and Nicolas Boulant1
1DRF/Joliot/Neurospin, CEA - Université Paris Saclay, Gif sur Yvette, France
1DRF/Joliot/Neurospin, CEA - Université Paris Saclay, Gif sur Yvette, France
he
Virtual Observation Points compression problem is reformulated to
further reduce by a factor ~5 the number of SAR matrices used for RF
pulse design and exam supervision.
Number
of VOPs computed for different overestimation factors λ.
Blue: Lee’s generalized VOP compression method, red: this work.
10g-SAR
computed over the uncompressed set of voxels and over the VOPs for
the two different methods (λ=0.7)
and for 1 million random RF shims. a) 10g-SAR over the VOPs versus
the true SAR. The dashed black line is the identity line. b) Boxplots
of the relative overestimation for the two methods. The SAR is never
underestimated.