Xiao-Long Wu1, Jiading Gai2, Fan
Lam1,2, Maojing Fu1,2, Justin P. Haldar1,2,
Yue Zhuo2,3, Zhi-Pei Liang1,2, Wen-Mei Hwu1,2,
Bradley P. Sutton2,3
1Electrical & Computer
Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United
States; 2Beckman Institute, University of Illinois at
Urbana-Champaign, Urbana, IL, United States; 3Bioengineering
Department, University of Illinois at Urbana-Champaign, Urbana, IL, United
States
Despite advances in acquisition and reconstruction technologies, typical clinical scans rely on Cartesian acquisitions and limited reconstruction routines. Requirements for significant computational resources and specialized expertise are a barrier to widespread use of algorithms that combine efficient non-Cartesian trajectories, field inhomogeneity correction, parallel imaging, and image regularization. We present a parallel implementation of such a reconstruction utilizing manycore graphics processing cards to speed reconstruction to acceptable levels, even for large matrix sizes and multiple coil acquisitions. We compare reconstruction times with parallel C-code and a common approximation method, showing that the proposed code is faster without using interpolation operators.