GPU Acceleration of PROPELLER MRI Using CUDA
PROPELLER technique can effectively cancel motion artifacts in MRI. But its wider application in clinical situation is limited due to considerable reconstruction times. Since most correction operations in PROPELLER reconstruction can be done for each strip respectively, the algorithm is highly parallelizable. This allows us to exploit the data-parallel nature of the GPU fragment processors. The paper presents an implementation to accelerate reconstruction of PROPELLER MRI on graphics processing units (GPUs) using CUDA. An improved grid-driven interpolation algorithm for PROPELLER trajectory is proposed for real-time imaging applications. The experiments show that the reconstruction is speeded up about nine times on GPU that of implementation on CPU with compatible motion correction accuracy and image quality.
PROPELLER griding GPU motion artifact motion correction
Hongyu Guo Jianping Dai Hongyu Guo Yanfa He
School of Biomedical & Information Engineering Northeastern University Shenyang,China Beijing Tiantan Hospital Beijing,China School of Electrical Engineering Shenyang University of Technology Shenyang,China School of Physics Northeast University Shenyang,China
国际会议
北京
英文
1-4
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）