A penalized-likelihood image reconstruction method for emission tomography, compared to postsmoothed maximum-likelihood with matched spatial resolution
A penalized-likelihood image reconstruction method for emission tomography, compared to postsmoothed maximum-likelihood with matched spatial resolution
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DOI：
10.1109/tmi.2003.816960
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发表时间：
2003-09-01
影响因子：
10.6
通讯作者：
Fessler, JA
中科院分区：
文献类型：
--
作者：
Nuyts, J;Fessler, JA
正则化对于发射断层成像中的图像重建是期望的。一种强大的正则化方法是惩罚似然（PL）重建算法（或等效地，最大后验重建），其中优化了似然和噪声抑制惩罚项（或贝叶斯先验）的总和。通常，这种方法会产生位置相关的分辨率和偏差。然而，对于发射断层摄影中的一些应用，平移不变的点扩散函数将是有利的。最近，已经提出了一种新的方法，在该方法中，在每个像素中调整惩罚项以施加均匀的局部脉冲响应。在本文中，提出了另一种方法来调整惩罚项。我们进行了正电子发射断层扫描和单光子发射计算机断层扫描模拟的新方法的postsmoothed最大似然（ML）的方法，使用前一种方法的脉冲响应作为后者的postsmoothing滤波器的性能进行比较。对于该实验，PL算法的噪声特性并不上级后平滑ML重建的噪声特性。
Regularization is desirable for image reconstruction in emission tomography. A powerful regularization method is the penalized-likelihood (PL) reconstruction algorithm (or equivalently, maximum a posteriori reconstruction), where the sum of the likelihood and a noise suppressing penalty term (or Bayesian prior) is optimized. Usually, this approach yields position-dependent resolution and bias. However, for some applications in emission tomography, a shift-invariant point spread function would be advantageous. Recently, a new method has been proposed, in which the penalty term is tuned in every pixel to impose a uniform local impulse response. In this paper, an alternative way to tune the penalty term is presented. We performed positron emission tomography and single photon emission computed tomography simulations to compare the performance of the new method to that of the postsmoothed maximum-likelihood (ML) approach, using the impulse response of the former method as the postsmoothing filter for the latter. For this experiment, the noise properties of the PL algorithm were not superior to those of postsmoothed ML reconstruction.