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Abstract #2942

Multi-GPU Implementation for Iterative MR Image Reconstruction with Field Correction

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.