Fast, accurate and shift-varying line projections for iterative reconstruction using the GPU.
Fast, accurate and shift-varying line projections for iterative reconstruction using the GPU.
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DOI：
10.1109/tmi.2008.2006518
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发表时间：
2009-03
影响因子：
10.6
通讯作者：
Levin CS
中科院分区：
文献类型：
--
作者：
Pratx G;Chinn G;Olcott PD;Levin CS
列表模式处理为发射层析成像迭代图像重建提供了一种处理稀疏投影的有效方法。一个经常被报道的问题是这种算法所需的巨大计算量。每个记录的事件都需要几个前后直线投影。研究了利用可编程图形处理单元(GPU)加速正电子发射断层扫描(PET)的直线投影运算，实现全3D列表模式有序子集期望最大化。我们设计了一种结合分辨率核的重建方法，它模拟了与光子发射、传输和检测相关的空间变化的物理过程。我们的开发特别适用于投影数据稀疏的应用，如高分辨率、动态和飞行时间PET重建。在图像质量和精确度几乎相同的情况下，GPU方法的运行速度比同等的CPU实现快50多倍。本文详细描述了如何使用GPU来加速直线投影操作，即使在响应线具有任意端点位置和使用移位可变分辨率核的情况下也是如此。为了验证这种新方法的正确性，文中还给出了一个定量评估。
List-mode processing provides an efficient way to deal with sparse projections in iterative image reconstruction for emission tomography. An issue often reported is the tremendous amount of computation required by such algorithm. Each recorded event requires several back- and forward line projections. We investigated the use of the programmable graphics processing unit (GPU) to accelerate the line-projection operations and implement fully-3D list-mode ordered-subsets expectation-maximization for positron emission tomography (PET). We designed a reconstruction approach that incorporates resolution kernels, which model the spatially-varying physical processes associated with photon emission, transport and detection. Our development is particularly suitable for applications where the projection data is sparse, such as high-resolution, dynamic, and time-of-flight PET reconstruction. The GPU approach runs more than 50 times faster than an equivalent CPU implementation while image quality and accuracy are virtually identical. This paper describes in details how the GPU can be used to accelerate the line projection operations, even when the lines-of-response have arbitrary endpoint locations and shift-varying resolution kernels are used. A quantitative evaluation is included to validate the correctness of this new approach.