Xu Fang, Mueller Klaus
Center for Visual Computing, Computer Science Department, Stony Brook University, Stony Brook, NY 11794-4400, USA.
Phys Med Biol. 2007 Jun 21;52(12):3405-19. doi: 10.1088/0031-9155/52/12/006. Epub 2007 May 17.
The recent emergence of various types of flat-panel x-ray detectors and C-arm gantries now enables the construction of novel imaging platforms for a wide variety of clinical applications. Many of these applications require interactive 3D image generation, which cannot be satisfied with inexpensive PC-based solutions using the CPU. We present a solution based on commodity graphics hardware (GPUs) to provide these capabilities. While GPUs have been employed for CT reconstruction before, our approach provides significant speedups by exploiting the various built-in hardwired graphics pipeline components for the most expensive CT reconstruction task, backprojection. We show that the timings so achieved are superior to those obtained when using the GPU merely as a multi-processor, without a drop in reconstruction quality. In addition, we also show how the data flow across the graphics pipeline can be optimized, by balancing the load among the pipeline components. The result is a novel streaming CT framework that conceptualizes the reconstruction process as a steady flow of data across a computing pipeline, updating the reconstruction result immediately after the projections have been acquired. Using a single PC equipped with a single high-end commodity graphics board (the Nvidia 8800 GTX), our system is able to process clinically-sized projection data at speeds meeting and exceeding the typical flat-panel detector data production rates, enabling throughput rates of 40-50 projections s(-1) for the reconstruction of 512(3) volumes.
近期出现的各类平板X射线探测器和C型臂机架,使得构建适用于多种临床应用的新型成像平台成为可能。这些应用中的许多都需要交互式3D图像生成,而基于CPU的廉价PC解决方案无法满足这一需求。我们提出了一种基于商用图形硬件(GPU)的解决方案来提供这些功能。虽然GPU此前已用于CT重建,但我们的方法通过利用各种内置的硬连线图形流水线组件来处理最耗时的CT重建任务——反投影,从而实现了显著的加速。我们表明,这样实现的计时结果优于仅将GPU用作多处理器时获得的计时结果,且重建质量没有下降。此外,我们还展示了如何通过平衡流水线组件之间的负载来优化跨图形流水线的数据流。结果是一个新颖的流式CT框架,该框架将重建过程概念化为跨计算流水线的稳定数据流,在获取投影后立即更新重建结果。使用配备单个高端商用图形卡(英伟达8800 GTX)的单台PC,我们的系统能够以达到并超过典型平板探测器数据生成速率的速度处理临床规模的投影数据,对于512(3)体积的重建,实现40 - 50帧/秒的吞吐率。