单片晶体在SiPM阵列上的原型系统与相互作用深度估计

J. Cabello, J. Gillam, J. Oliver, J. Barrio, M. Rafecas, G. Llosá
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引用次数: 1

摘要

提高灵敏度是新型探测器发展的主要挑战之一。虽然像素化晶体是标准的,使用连续晶体可以提供增加的活动体积,从而提高灵敏度。连续晶体中光子相互作用位置的精确估计需要复杂的算法。此外,在重建过程中加入相互作用深度(Dol)可以减轻视场边缘附近的视差影响,因此Dol估计是非常可取的。在这项工作中,在没有额外硬件、训练数据集或蒙特卡罗模拟的情况下,根据已经存在的分析模型估计3D中的相互作用位置坐标。该算法是在一个由连续晶体与SiPM阵列耦合组成的双探测头系统中实现的。获取的数据以列表模式存储,其中保留了交互位置的连续性质。对于图像重建,由于晶体是连续的,系统矩阵元素的预计算将需要对检测到的测量进行离散化。为了避免数据离散化,系统矩阵元素的计算是动态的。在重建算法中,利用类似siddon的算法保留空间信息,其中射线端点对应于连续空间中估计的相互作用位置,在系统矩阵元素的计算中引入了相互作用位置估计的不确定性。将连续数据重建与人工离散数据重建进行了比较。结果表明,用连续晶体获得的ML-EM重构点源的空间分辨率优于用像素化晶体获得的空间分辨率。
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Monolithic crystals on SiPM arrays in a prototype system with depth of interaction estimation
Increased sensitivity is one of the major challenges in novel detector development. While pixelated crystals are standard, the use of continuous crystals can provide increased active volume and thus sensitivity. Accurate estimation of the interaction positions of photons in continuous crystals requires a sophisticated algorithm. Additionally, including depth of interaction (Dol) in the reconstruction process can mitigate parallax effects near the edges of field of view, therefore Dol estimation is highly desirable. In this work, the interaction position coordinates in 3D are estimated adapting an already existing analytical model to our system with no additional hardware, training data sets or Monte Carlo simulations. The algorithm is implemented in a two-detector-head system comprised of continuous crystals coupled to SiPM arrays. Acquired data is stored in list-mode where the continuous nature of the interaction position is preserved. For image reconstruction, since the crystal is continuous, pre-computation of the system matrix elements would require discretization of the detected measurements. To avoid data discretization the system matrix elements are calculated on-the-fly. Spatial information is later on retained in the reconstruction algorithm by using a Siddon-like algorithm where the ray end-points correspond to the estimated interaction positions in continuous space, introducing the interaction position estimation uncertainty in the calculation of the system matrix elements. Reconstruction using continuous data is compared to reconstruction using artificially discretized data. Results show that the spatial resolution measured from a reconstructed point source using ML-EM obtained with a continuous crystal is superior to the spatial resolution obtained with a pixelated crystal.
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