Locations of discontinuities as priors for improved Bayesian reconstructions from projections (emission tomography)

M. Lee, G. Gindi, Anand Rangarajan, I. Zubal
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Abstract

A Bayesian image reconstruction method from projection data using explicit discontinuity locations as priors is proposed. The algorithm seeks smooth solutions with occasional discontinuities with a special coupling term that influences the creation of discontinuities in the vicinity of the significant locations. It is shown that the reconstruction corresponds to the use of a generic piecewise smoothness constraint. The model incorporates prior knowledge of discontinuity location into a reconstruction algorithm. The results appear favorable.<>
不连续点的位置作为先验的改进贝叶斯投影重建(发射层析成像)
提出了一种以明确的不连续点为先验的投影数据贝叶斯图像重建方法。该算法寻求具有偶然性不连续的平滑解,并具有影响重要位置附近不连续产生的特殊耦合项。结果表明,重构对应于一般分段平滑约束的使用。该模型将不连续点定位的先验知识引入到重构算法中。结果似乎是有利的。
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