Moore Jared W, Barrett Harrison H, Furenlid Lars R
College of Optical Sciences, University of Arizona, Tucson, AZ 85724 USA.
Department of Radiology and College of Optical Sciences, University of Arizona, Tucson, AZ 85724 USA.
IEEE Nucl Sci Symp Conf Rec (1997). 2009;2009:4154-4157. doi: 10.1109/NSSMIC.2009.5402313.
We have developed a flexible x-ray micro-CT system, named FaCT, capable of changing its geometric configuration and acquisition protocol in order to best suit an object being imaged for a particular diagnostic task. High-performance computing technologies have been a major enabling factor for this adaptive CT system in terms of system control, fast reconstruction, and data analysis. In this work, we demonstrate an adaptive procedure in which a quick, sparse-projection pre-scan is performed, the data are reconstructed, and a region of interest is identified. Next, a diagnostic-quality scan is performed where, given the region of interest, the control computer calculates an illumination window for on-line control of an x-ray source masking aperture to transmit radiation only through the region of interest throughout the scan trajectory. Finally, the diagnostic scan data are reconstructed, with the region of interest being clearly resolved. We use a combination of a multi-core CPU and a pair of NVIDIA Tesla GPUs to perform these tasks.
我们开发了一种名为FaCT的灵活X射线微型计算机断层扫描（micro-CT）系统，该系统能够改变其几何配置和采集协议，以便最适合针对特定诊断任务成像的物体。在系统控制、快速重建和数据分析方面，高性能计算技术一直是这种自适应CT系统的主要促成因素。在这项工作中，我们展示了一种自适应程序，其中先进行快速、稀疏投影预扫描，重建数据，然后识别感兴趣区域。接下来，进行诊断质量扫描，在已知感兴趣区域的情况下，控制计算机计算一个照明窗口，用于在线控制X射线源掩膜孔径，以便在整个扫描轨迹中仅使辐射透过感兴趣区域。最后，重建诊断扫描数据，感兴趣区域得到清晰分辨。我们使用多核CPU和一对NVIDIA Tesla GPU的组合来执行这些任务。
