GPU accelerated FDTD solver and its application in MRI

Abstract

The finite difference time domain (FDTD) method is a popular technique for computational electromagnetics (CEM). The large computational power often required, however, has been a limiting factor for its applications. In this paper, we will present a graphics processing unit (GPU)-based parallel FDTD solver and its successful application to the investigation of a novel B1 shimming scheme for high-field magnetic resonance imaging (MRI). The optimized shimming scheme exhibits considerably improved transmit B(1) profiles. The GPU implementation dramatically shortened the runtime of FDTD simulation of electromagnetic field compared with its CPU counterpart. The acceleration in runtime has made such investigation possible, and will pave the way for other studies of large-scale computational electromagnetic problems in modern MRI which were previously impractical.

Model forB1Imaging in MRI Using the Rotating RF Field

“…Figures 2 , 4 , and 8 demonstrate that the B 1 -RRFC could provide representative MR images without the application of transverse B 0 gradients. Since the numerical simulations take considerable time to be solved, it would be viable to accelerate the computation by a factor of up to one hundred by employing parallel computing or graphical processing units as detailed in [ 27 , 28 ]. The use of the pseudo-inverse to solve ( 4 ) results in intensity deviations from the original image that are smaller than when LSQR or Bloch-LSQR approaches are applied.…”

Medical image processing on the GPU – Past, present and future

“…Another important issue for high-field imaging is shimming, i.e. the removal of inhomogeneities in the magnetic field, which can also be computationally costly (Chi et al, 2010).…”