GPU-based high-performance computing for radiation therapy

被引:102
作者
Jia, Xun [1 ]
Ziegenhein, Peter [2 ,3 ]
Jiang, Steve B. [1 ]
机构
[1] Univ Texas SW Med Ctr Dallas, Deparment Radiat Oncol, Dallas, TX 75390 USA
[2] Inst Canc Res, Joint Dept Phys, Sutton SM2 5NG, Surrey, England
[3] Royal Marsden NHS Fdn Trust, Sutton SM2 5NG, Surrey, England
关键词
graphics processing units; high-performance computing; radiation therapy; CONE-BEAM CT; MONTE-CARLO-SIMULATION; DEFORMABLE IMAGE REGISTRATION; DIRECT APERTURE OPTIMIZATION; TRACK-REPEATING ALGORITHM; 3D TUMOR-LOCALIZATION; FAST DOSE CALCULATION; RECONSTRUCTION ALGORITHMS; ELECTRON-TRANSPORT; PROJECTION DATA;
D O I
10.1088/0031-9155/59/4/R151
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Recent developments in radiotherapy therapy demand high computation powers to solve challenging problems in a timely fashion in a clinical environment. The graphics processing unit (GPU), as an emerging high-performance computing platform, has been introduced to radiotherapy. It is particularly attractive due to its high computational power, small size, and low cost for facility deployment and maintenance. Over the past few years, GPU-based high-performance computing in radiotherapy has experienced rapid developments. A tremendous amount of study has been conducted, in which large acceleration factors compared with the conventional CPU platform have been observed. In this paper, we will first give a brief introduction to the GPU hardware structure and programming model. We will then review the current applications of GPU in major imaging-related and therapy-related problems encountered in radiotherapy. A comparison of GPU with other platforms will also be presented.
引用
收藏
页码:R151 / R182
页数:32
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