In this article, a new method to quantify the activity of spatially distributed gamma-emitting isotopes (hotspots) in homogenous content waste drums without the use of a collimator is presented. The method utilizes a spatial digital filter derived using maximum likelihood (ML) to determine multiple sources’ positions and then calculate their activities. To solve the multidimensional maximization problem, we use an alternating projection (AP) technique, which transforms the problem into a considerably simpler 1-D maximization problem. A dynamic grid search was developed to further decrease the computational load. The mathematical simulations demonstrate the improved accuracy when compared to that of industrial segmented gamma scanning (SGS) systems and the same accuracy as that of newer methods. Furthermore, the new method offers the benefit of replacing the heavy mechanical collimator with a “virtual collimator” formed by digital filters and an advanced algorithm to create a “digital virtual scan” of drum volume to locate hotspots.

中文翻译：

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用于放射性废物桶的无准直器无源伽马扫描

在本文中，介绍了一种无需使用准直器即可量化均质废物桶中空间分布的伽马发射同位素（热点）活动的新方法。该方法利用使用最大似然 (ML) 导出的空间数字滤波器来确定多个源的位置，然后计算它们的活动。为了解决多维最大化问题，我们使用交替投影 (AP) 技术，将问题转换为相当简单的一维最大化问题。开发了动态网格搜索以进一步减少计算负载。数学模拟表明，与工业分段伽马扫描 (SGS) 系统相比，精度有所提高，并且与较新方法的精度相同。此外，