Fang Xu and Klaus Mueller 2007 Phys. Med. Biol. 52 3405 doi:10.1088/0031-9155/52/12/006
Fang Xu and Klaus Mueller
Show affiliationsThe 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 5123 volumes.
Issue 12 (21 June 2007)
Received 16 November 2006, in final form 1 March 2007
Published 17 May 2007
Fang Xu and Klaus Mueller 2007 Phys. Med. Biol. 52 3405
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