Self-Organizing Map Neural Network-Based Depth-of-Interaction Determination for Continuous Crystal PET Detectors
Self-Organizing Map Neural Network-Based Depth-of-Interaction Determination for Continuous Crystal PET Detectors
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DOI：
10.1109/tns.2015.2421290
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发表时间：
2015-05
影响因子：
1.8
通讯作者：
Yonggang Wang;Liwei Wang;Deng Li;Xinyi Cheng;Yong Xiao
中科院分区：
文献类型：
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作者：
Yonggang Wang;Liwei Wang;Deng Li;Xinyi Cheng;Yong Xiao
对于基于连续晶体的 PET 探测器，通过闪烁光的单端读数，不仅可以精确估计相互作用点的二维 (2D) 平面坐标，还可以精确估计 γ 事件的相互作用深度 (DOI)。在本文中，我们提出了一种用于连续晶体 PET 探测器的 DOI 测定的实用方法。通过无监督学习的自组织映射（SOM）神经网络，将每个参考位置的垂直照射参考事件分为一定数量的组，同时用于平面坐标估计和DOI解码。在倾斜照射中测量的参考事件用于生成 SOM 神经元的初始权重并校准 DOI 解码。将新方法应用于我们的实验数据，基于 SOM 的 DOI 估计可以在晶体的整个厚度（0 - 10 mm）上实现 2.56 mm 的平均分辨率。 DOI 效应还可以通过比较不同入射角下测试光束在经过和不经过 DOI 校正的情况下的平面位置分辨率来评估。测试结果表明，DOI确定可以无缝集成到我们之前提出的基于SOM的平面坐标估计方案中，以实现基于连续晶体的PET探测器的高性能实时三维位置估计。
For continuous crystal-based PET detectors, not only the two-dimensional (2D) plane coordinate of the interaction point, but also the depth-of-interaction (DOI) of the γ event could be precisely estimated by the single-end readout of the scintillation light. In this paper, we propose a practical method for DOI determination for continuous crystal PET detectors. By self-organizing map (SOM) neural network with unsupervised learning, the perpendicularly irradiated reference events in each reference position are classified into a certain number of groups, which are simultaneously used for the plane coordinate estimation and the DOI decoding. The reference events measured in an oblique irradiation are used to generate the initial weights of the SOM neurons and to calibrate the DOI decoding. Applying the new method to our experimental data, the SOM-based DOI estimation could achieve an average resolution of 2.56 mm over the whole thickness (0 - 10 mm) of the crystal. The DOI effect is also evaluated by comparing the plane position resolutions of the test beams in different incident angles with and without the DOI correction. The test results show that the DOI determination could seamlessly integrate into our previously proposed the SOM-based plane coordinate estimation scheme to realize the high performance real-time three-dimensional position estimation for continuous crystal-based PET detectors.