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集装箱CT检测系统中贝叶斯图像重建算法的应用探讨
Bayesian reconstruction algorithms in the container CT inspection system
【摘要】 最大后验概率(Maximum a posteriori,MAP)图像重建算法是一种贝叶斯算法(Bayesian Re- construction,BR),可克服最大似然(Maximum Likelihood,ML)算法不能抑制噪声、重建时间较长的缺点。探讨了适合集装箱CT检测的两种MAP重建算法:加权最小二乘-最大后验概率-共轭梯度算法(weighted-least-squares MAP conjugate gradient,WLS-MAP-CG)和有序子集-贝叶斯算法(modified or- dered subset,MOS-BR)并讨论了合适的先验知识分布。
【Abstract】 The use of maximum a posteriori (MAP) image reconstruction algorithms in the container CT inspection system is discussed here. The MAP algorithms are superior than the EM-based algorithms both in noise reduction and the convergence speed. We choose two efficient MAP algorithms: one is weighted-least-squares MAP conjugate gradient algorithms (WLS-MAP-CG), the other is modified ordered subset Bayesian reconstruction (MOS-BR). Accompanied with the Gibbs prior, both approaches can be expected to produce smooth reconstruction images with good quantitative accuracy.
- 【文献出处】 核电子学与探测技术 ,Nuclear Electronics & Detection Technology , 编辑部邮箱 ,2006年02期
- 【分类号】TL81
- 【下载频次】117