Yue Zhuo1, Xiao-Long Wu2, Justin
P. Haldar2, Wen-mei W. Hwu2, Zhi-Pei Liang2,
Bradley P. Sutton1
1Bioengineering, University of Illinois
at Urbana-Champaign, Urbana, IL, United States; 2Electrical and
Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL,
United States
Nowadays
Graphics Processing Units (GPU) leads high computation performance in science
and engineering application. We propose a multi-GPU implementation for
iterative MR image reconstruction with magnetic field inhomogeneity
compensation. The imaging model includes the physics of field inhomogeneity
map and its gradients, and thus can compensate for both geometric distortion
and signal loss. The iterative reconstruction algorithm is realized on
C-language based on Compute Unified Device Architecture (CUDA). Result shows
the performance of multi-GPU gains significant speedup by two orders of
magnitude. Therefore, the fast implementation make the clinical and cognitive
science requirements are achievable for accurate MRI reconstruction.