PENALIZED WEIGHTED LEAST-SQUARES IMAGE-RECONSTRUCTION FOR POSITRON EMISSION TOMOGRAPHY
PENALIZED WEIGHTED LEAST-SQUARES IMAGE-RECONSTRUCTION FOR POSITRON EMISSION TOMOGRAPHY
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DOI：
10.1109/42.293921
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发表时间：
1994-06-01
影响因子：
10.6
通讯作者：
FESSLER, JA
中科院分区：
文献类型：
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作者：
FESSLER, JA
提出了一种基于惩罚加权最小二乘(PWLS)目标的正电子发射断层成像(PET)图像重建方法。对于对意外重合进行了预校正的正电子发射计算机断层扫描测量，我们在统计学上认为，最小二乘目标函数比流行的泊松似然目标函数更合适。我们提出了一种简单的基于数据的方法来确定考虑衰减和探测器效率的权重。一种非负的逐次超松弛(+SOR)算法快速收敛到PWLS目标的全局最小值。定量仿真结果表明，与最大似然期望最大化(ML-EM)方法相比，pwls+SOR方法的偏差/方差权衡性能相当(但迭代次数更少)，而相对于传统的滤波反投影(FBP)方法有所改善。定性结果表明，PWLS+SOR方法几乎消除了FBP方法常见的条纹伪影，并表明所提出的测量值加权方法是改进FBP方法的一个重要因素。
This paper presents an image reconstruction method for positron-emission tomography (PET) based on a penalized, weighted least-squares (PWLS) objective. For PET measurements that are precorrected for accidental coincidences, we argue statistically that a least-squares objective function is as appropriate, if not more so, than the popular Poisson likelihood objective. We propose a simple data-based method for determining the weights that accounts for attenuation and detector efficiency. A non-negative successive over-relaxation (+SOR) algorithm converges rapidly to the global minimum of the PWLS objective. Quantitative simulation results demonstrate that the bias/variance trade-off of the PWLS+SOR method is comparable to the maximum-likelihood expectation-maximization (ML-EM) method (but with fewer iterations), and is improved relative to the conventional filtered backprojection (FBP) method. Qualitative results suggest that the streak artifacts common to the FBP method are nearly eliminated by the PWLS+SOR method, and indicate that the proposed method for weighting the measurements is a significant factor in the improvement over FBP.