A survey of GPU-based acceleration techniques in MRI reconstructions

被引:46
作者
Wang, Haifeng [1 ]
Peng, Hanchuan [2 ]
Chang, Yuchou [3 ]
Liang, Dong [1 ]
机构
[1] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China
[2] Allen Inst Brain Sci, Seattle, WA USA
[3] Univ Houston Downtown, Comp Sci & Engn Technol Dept, Houston, TX USA
基金
中国国家自然科学基金;
关键词
Graphics processing unit (GPU); magnetic resonance imaging (MRI); reconstruction; GRAPHICS; PERFORMANCE; ALGORITHM; IMPATIENT; SENSE; CUDA;
D O I
10.21037/qims.2018.03.07
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Image reconstruction in magnetic resonance imaging (MRI) clinical applications has become increasingly more complicated. However, diagnostic and treatment require very fast computational procedure. Modern competitive platforms of graphics processing unit (GPU) have been used to make high-performance parallel computations available, and attractive to common consumers for computing massively parallel reconstruction problems at commodity price. GPUs have also become more and more important for reconstruction computations, especially when deep learning starts to be applied into MRI reconstruction. The motivation of this survey is to review the image reconstruction schemes of GPU computing for MRI applications and provide a summary reference for researchers in MRI community.
引用
收藏
页码:196 / 208
页数:13
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