基于CPU-GPU平台的三维多片分支曲面重构性能研究

N. A. Hadi, N. Alias
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摘要

本文提出了一种基于CPU-GPU的三维分支曲面复合轮廓生成算法。复合轮廓是基于基于和分支轮廓的数据点生成的,并位于两个轮廓之间。距离计算是复合轮廓生成中消耗CPU时间最多的过程之一,因此选择在GPU上执行该过程。然后将所提出的基于CPU-GPU平台的复合轮廓生成方法应用于斯坦福兔和人体骨盆的CT图像,每段曲线点的个数不同。这些样本总共生成了12个复合轮廓。根据处理时间和加速速度来衡量所开发算法的性能。结果表明,CPU-GPU算法的速度提升高达150倍。
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The Performance of 3D Multi-slice Branched Surface Reconstruction on CPU-GPU Platform
: In this paper, a CPU-GPU algorithm to generate composite contour for 3D branching surface is presented. The composite contour is generated based on the data points from based and branched contours and located in between the two contours. Distance calculation is one of the processes in composite contour generation which consumes the most CPU time, therefore, this process is chosen to be executed on the GPU. The developed composite contour generation method on the CPU-GPU platform is then applied on CT images of Stanford bunny and human pelvic with three different number of curve points per segment. These samples generate 12 composite contours in total. The performance of the developed algorithm is measured based on the processing time and the speedup. The result shows that the CPU-GPU algorithm has improved the speedup as high as 150 times.
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