Towards real-time radiation therapy: GPU accelerated superposition/convolution

被引:42
作者
Jacques, Robert [1 ]
Taylor, Russell [2 ]
Wong, John [1 ]
McNutt, Todd [1 ]
机构
[1] Johns Hopkins Univ, Sch Med, Baltimore, MD 21231 USA
[2] Johns Hopkins Univ, Dept Comp Sci, Baltimore, MD 21218 USA
基金
美国国家科学基金会;
关键词
Convolution/superposition; Radiation therapy planning; Graphics processing unit (GPU); Inverse planning; Adaptive radiotherapy; CONVOLUTION METHOD; DOSE CALCULATION; MODULATED ARC; PHOTON BEAMS; ENERGY; CONVOLUTION/SUPERPOSITION; KERNELS;
D O I
10.1016/j.cmpb.2009.07.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We demonstrate the use of highly parallel graphics processing units (GPUs) to accelerate the superposition/convolution (S/C) algorithm to interactive rates while reducing the number of approximations. S/C first transports the incident fluence to compute the total energy released per unit mass (TERMA) grid. Dose is then calculated by superimposing the dose deposition kernel at each point in the TERMA grid and summing the contributions to the surrounding voxels. The TERMA algorithm was enhanced with physically correct multi-spectral attenuation and a novel inverse formulation for increased performance, accuracy and simplicity. Dose deposition utilized a tilted poly-energetic inverse cumulative-cumulative kernel, with the novel option of using volumetric mip-maps to approximate solid angle ray casting. Exact radiological path ray casting decreased discretization errors. We achieved a speedup of 34x-98x over a highly optimized CPU implementation. (C) 2009 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:285 / 292
页数:8
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