用AB-EMML进行低统计量重建

K. Erlandsson, D. Visvikis, W. Waddington, I. Cullum, P. Jarritt, L. S. Polowsky
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引用次数: 21

摘要

在动态SPECT研究中,每个时间框架的采集时间较短,获得的数据具有非常低的统计量。对于这种情况,基于乘法校正因子的标准迭代重建算法(自动包括非负性约束)可能不是理想的。AB-EMML算法允许用户在图像值的上界和下界上包含先验信息。我们使用该算法与负下界重建低统计量SPECT数据,以允许负图像值。我们的结果表明,这种方法可以在低计数水平下保持定量准确性,而标准方法会产生偏差值。此外,噪声分布更加均匀,在高强度区域较低,在低强度区域较高。趋同通常较慢,但在寒冷地区更快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Low-statistics reconstruction with AB-EMML
In dynamic SPECT studies with short acquisition times per time-frame, data with very low-statistics is obtained. For such cases standard iterative reconstruction algorithms based on multiplicative correction factors, automatically including a non-negativity constraint, might not be Ideal. The AB-EMML algorithm allows the user to include prior information on the upper and lower bounds for the image values. We have used this algorithm with a negative lower bound for reconstruction of low-statistics SPECT data in order to allow for negative image values. Our results show that this method can preserve quantitative accuracy at low count levels, where standard methods produces biased values. Furthermore, the noise is much more uniformly distributed-lower in high intensity regions and higher in low intensity regions. The convergence is generally slower, but faster in cold regions.
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