基于cuda的三次b样条体射线投射

Changgong Zhang, P. Xi, C. Zhang
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引用次数: 12

摘要

基于gpu的体射线投射可以为交互式医学可视化提供高性能。沿着射线采集的样本越多,即采样率越高,我们就越能准确地表示体积数据,特别是当体积和传递函数的组合频率很高时。然而,这将大大降低渲染性能,因为更多的样本意味着更耗时的GPU内存访问。在本文中,我们提出了一种有效的体射线投射算法,它可以在一个射线段内使用三次b样条进行更多的采样。这可以提高采样率,提供高质量的图像,而不会出现明显的性能下降。此外,我们的算法根本不需要调整其他任何东西。这个事实保证了它的灵活性和简单性。我们利用新的编程接口CUDA来实现光线投射,而不是传统的片段着色器。实验结果表明,该方法可以作为一种有效的医学可视化工具。
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CUDA-Based Volume Ray-Casting Using Cubic B-spline
GPU-based volume ray-casting can provide high performance for interactive medical visualization. The more samples we take along rays, i.e., a higher sampling rate, the more accurately we can represent the volume data, especially when the combined frequency of the volume and transfer function is high. However, this will reduce the rendering performance considerably because more samples mean more time-consuming memory access on GPU. In this paper, we propose an effective volume ray-casting algorithm which can perform more samplings within a ray segment using cubic B-spline. This can improve the sampling rate and offer high quality images without obvious performance degradation. Besides, our algorithm does not have to adjust anything else at all. This fact guarantees its flexibility and simplicity. We exploit the new programming interface CUDA to implement ray-casting rather than conventional fragment shader. Experimental results prove this method can be used as an effective medical visualization tool.
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