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    基于CUDA的GPU加速代数迭代重建算法

    Accelerating Simultaneous Algebraic Reconstruction Technique Based on CUDA-Enabled GPU

    • 摘要: CT迭代重建算法多用于投影数据不完备的情况,但迭代重建算法在普通计算机上的计算非常耗时,主要源于需要反复地进行投影与反投影计算。为此,文章提出了一种基于NVIDIA统一计算设备架构(CUDA)的联合代数重建加速方法。采用基于射线驱动和基于体素驱动的方法分别加速投影与反投影过程。试验结果显示,在不影响重建图像质量的基础上,重建时间大大减少,具有工程应用价值。

       

      Abstract: Iterative methods is a popular choice in image reconstruction fields due to its capability of recovering object information from incomplete acquisition data. However, it is computationally expensive due to frequent uses of forward and backward projections. In this paper, a method of accelerating SART based on CUDA-enabled GPU was proposed. We introduced a ray-driven method for forward projection and a voxel-driven approach for backward projection. The experimental results showed that the reconstructed images quality was not affected, but the reconstruction time was greatly decreased.

       

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