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
相关论文
共 50 条
  • [1] Towards real-time radiation therapy: Superposition/convolution at interactive rates
    Jacques, R. A.
    Taylor, R. H.
    Wong, J. W.
    McNutt, T. R.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2008, 72 (01): : S667 - S667
  • [2] Towards Real-Time Radiation Therapy: Superposition/Convolution at 4fps
    Jacques, R.
    Taylor, R.
    Wong, J.
    McNutt, T.
    MEDICAL PHYSICS, 2008, 35 (06)
  • [3] Real-time dose computation: GPU-accelerated source modeling and superposition/convolution
    Jacques, Robert
    Wong, John
    Taylor, Russell
    McNutt, Todd
    MEDICAL PHYSICS, 2011, 38 (01) : 294 - 305
  • [4] Real-time massive convolution for audio applications on GPU Massive convolution on GPU
    Belloch, Jose A.
    Gonzalez, Alberto
    Martinez-Zaldivar, F. J.
    Vidal, Antonio M.
    JOURNAL OF SUPERCOMPUTING, 2011, 58 (03): : 449 - 457
  • [5] Towards real-time DNA biometrics using GPU-accelerated processing
    Reja, Mario
    Pungila, Ciprian
    Negru, Viorel
    LOGIC JOURNAL OF THE IGPL, 2021, 29 (06) : 906 - 924
  • [6] Real-time massive convolution for audio applications on GPUMassive convolution on GPU
    Jose A. Belloch
    Alberto Gonzalez
    F. J. Martínez-Zaldívar
    Antonio M. Vidal
    The Journal of Supercomputing, 2011, 58 : 449 - 457
  • [7] Multi-Energetic, GPU-Accelerated Superposition/Convolution
    Jacques, R.
    Taylor, R.
    Wong, J.
    McNutt, T.
    MEDICAL PHYSICS, 2011, 38 (06)
  • [8] GPU-accelerated real-time stixel computation
    Hernandez-Juarez, Daniel
    Espinosa, Antonio
    Moure, Juan C.
    Vazquez, David
    Lopez, Antonio M.
    2017 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2017), 2017, : 1054 - 1062
  • [9] Geocube – GPU accelerated real-time rendering of transparency and translucency
    Bin Chan
    Wenping Wang
    The Visual Computer, 2005, 21 : 579 - 590
  • [10] Validation of GPU-accelerated superposition-convolution dose computations for the Small Animal Radiation Research Platform
    Cho, Nathan
    Tsiamas, Panagiotis
    Velarde, Esteban
    Tryggestad, Erik
    Jacques, Robert
    Berbeco, Ross
    McNutt, Todd
    Kazanzides, Peter
    Wong, John
    MEDICAL PHYSICS, 2018, 45 (05) : 2252 - 2265