CUDA Papers

A collection of research papers and projects utilizing CUDA technology

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


Many advanced MRI image acquisition and reconstruction methods see limited application due to high computational cost in MRI. For instance,iterative reconstruction algorithms (e.g. non-Cartesian k-space trajectory, or magnetic field inhomogeneity compensation) can improve image qualitybut suffer from low reconstruction speed. General-purpose computing on graphics processing units (GPU) have demonstrated significantperformance speedups and cost reductions in science and engineering applications. In fact, GPU can offer significant speedup due to MRIparallelized-data structure, e.g. multi-shots, multi-coil, multi-slice, multi-time-point, etc. We propose an implementation of iterative MR imagereconstruction with magnetic field inhomogeneity compensation on multi-GPUs. The MR image model is based on non-Cartesian trajectory (i.e.spiral) in k-space, and can compensate for both geometric distortion and some signal loss induced by susceptibility gradients.


Y. Zhuo, Bioengineering, University of Illinois at Urbana-Champaign

X-L. Wu, J. P. Haldar, W-M. W. Hwu, Z-P. Liang, Electrical and Computer Engineering, University of Illinois atUrbana-Champaign

B. P. Sutton, Bioengineering, University of Illinois at Urbana-Champaign

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