Miller Brian W, Van Holen Roel, Barrett Harrison H, Furenlid Lars R
Center for Gamma-Ray Imaging and the College of Optical Sciences, University of Arizona, Tucson, AZ 85724 USA.
MEDISIP, Department of Electronics and Information Systems, Ghent University, B-9000 Ghent, Belgium. He is supported by a postdoctoral fellowship of the Research Foundation (FWO).
IEEE Nucl Sci Symp Conf Rec (1997). 2011 Oct;2011:3548-3553. doi: 10.1109/NSSMIC.2011.6153666. Epub 2011 Oct 23.
Recently, high-resolution gamma cameras have been developed with detectors containing> 10-10 elements. SPECT imagers based on these detectors usually also have a large number of voxel bins and therefore face memory storage issues for the system matrix when performing fast tomographic reconstructions using iterative algorithms. To address these issues, we have developed a method that parameterizes the detector response to a point source and generates the system matrix on the fly during MLEM or OSEM on graphics hardware. The calibration method, interpolation of coefficient data, and reconstruction results are presented in the context of a recently commissioned small-animal SPECT imager, called FastSPECT III.
最近，已开发出具有包含超过10¹⁰个元素探测器的高分辨率伽马相机。基于这些探测器的单光子发射计算机断层显像（SPECT）成像仪通常也有大量的体素仓，因此在使用迭代算法进行快速断层重建时，系统矩阵面临内存存储问题。为了解决这些问题，我们开发了一种方法，该方法对探测器对点源的响应进行参数化，并在图形硬件上的最大似然期望最大化（MLEM）或有序子集期望最大化（OSEM）过程中即时生成系统矩阵。校准方法、系数数据插值和重建结果是在最近启用的名为FastSPECT III的小动物SPECT成像仪的背景下呈现的。
