Hesterman Jacob Y, Caucci Luca, Kupinski Matthew A, Barrett Harrison H, Furenlid Lars R
Bioscan, Inc., Washington, DC 20007 USA.
IEEE Trans Nucl Sci. 2010 Jun 1;57(3):1077-1084. doi: 10.1109/TNS.2010.2045898.
A fast search algorithm capable of operating in multi-dimensional spaces is introduced. As a sample application, we demonstrate its utility in the 2D and 3D maximum-likelihood position-estimation problem that arises in the processing of PMT signals to derive interaction locations in compact gamma cameras. We demonstrate that the algorithm can be parallelized in pipelines, and thereby efficiently implemented in specialized hardware, such as field-programmable gate arrays (FPGAs). A 2D implementation of the algorithm is achieved in Cell/BE processors, resulting in processing speeds above one million events per second, which is a 20× increase in speed over a conventional desktop machine. Graphics processing units (GPUs) are used for a 3D application of the algorithm, resulting in processing speeds of nearly 250,000 events per second which is a 250× increase in speed over a conventional desktop machine. These implementations indicate the viability of the algorithm for use in real-time imaging applications.
介绍了一种能够在多维空间中运行的快速搜索算法。作为一个示例应用，我们展示了它在二维和三维最大似然位置估计问题中的效用，该问题出现在处理光电倍增管（PMT）信号以推导紧凑型伽马相机中的相互作用位置时。我们证明该算法可以在流水线中并行化，从而在诸如现场可编程门阵列（FPGA）等专用硬件中高效实现。该算法的二维实现是在Cell/BE处理器中完成的，处理速度超过每秒一百万个事件，比传统台式机快20倍。图形处理单元（GPU）用于该算法的三维应用，处理速度接近每秒250,000个事件，比传统台式机快250倍。这些实现表明了该算法用于实时成像应用的可行性。
