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康普顿相机用于γ射线成像具有装置轻便、探测效率高和成像能区广的优点. 然而, 由于探测系统难以分辨康普顿散射事件和散射光子吸收事件, 造成图像重建错误. 使用GEANT4蒙特卡罗程序构建了基于三维位置灵敏碲锌镉探测器的康普顿相机模型, 模拟探测远场137Cs点源特征γ射线并逐个事件地记录探测器中发生相互作用的位置和沉积的能量. 使用反投影图像重建算法对有效康普顿散射事件的康普顿散射角进行重建并对放射源成像, 研究了事件顺序重建对成像分辨的影响. 结果表明, 错误排序事件对成像分辨的影响主要在偏离源点位置30°以内的区域, 源点位置附近产生的错误重建像点在26°附近形成环状分布. 使用基于沉积能量大小的康普顿边缘测试和简单比较法对事件进行排序, 正确排序事件的比例提升至82%, 源点位置的像点分布密度提升了47%, 成像分辨得到了提升.The Compton camera for γ-ray imaging has the advantages of light weight, high detection efficiency, and wide imaging energy range. However, it is difficult for the detection system to distinguish between the Compton scattering event and scattering photon absorption event, which results in erroneous image reconstruction. In this work, a simulation model of Compton camera based on a three-dimensional position-sensitive CdZnTe detector is constructed using GEANT4 program. The detection of characteristic γ-ray from a far-field 137Cs point-like source is simulated. The location of the interaction and energy deposition in the detector are recorded by means of event-by-event. The Compton scattering angles of effective Compton scattering events and imaging of the radioactive source are reconstructed using a simple back-projection algorithm which is an image reconstruction algorithm suitable for real-time imaging scenes. The influences of event sequence reconstruction on the imaging resolution and its improvement are investigated. The results show that the influence of incorrect sequence events on imaging resolution is mainly in the area within 30° deviation from the source position, resulting in a decrease in the density of the image points distributed at the source position. Incorrectly reconstructed image points are generated near the source position and form a ring at 26°. The percentage of correctly sequenced events increases to 82% by using Compton edge test and simple comparison method based on the deposited energy for sequencing events. The density of image points distributed at the source location is improved by 47%, and the incorrect reconstruction of the image point distribution near the source location is greatly suppressed, resulting in an improved imaging resolution. The research results provide support for designing Compton camera and optimizing image reconstruction.
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Keywords:
- Compton camera /
- GEANT4 /
- sequence reconstruction /
- imaging resolution
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图 1 康普顿散射及γ射线入射方向重建示意图
Fig. 1. Schematic of Compton scattering and γ-ray incidence direction reconstruction.
图 2 简单反投影图像重建算法示意图
Fig. 2. Schematic of the simple back-projection image reconstruction algorithm.
图 4 正确排序事件的散射光子能量与康普顿散射角的分布
Fig. 4. Distribution of scattering photon energy and Compton scattering angles for correctly sequenced events.
图 5 正确排序事件和混乱排序事件的散射光子能量分布
Fig. 5. Scattering photon energy distribution for correct and scrambled sequence events.
图 6 正确排序事件和错误排序事件的反投影康普顿圆锥示意图
Fig. 6. Schematic of the back-projection Compton cone for correct and incorrect sequence events.
图 7 错误排序事件的反投影康普顿散射角与正确重建所需康普顿散射角的差异分布
Fig. 7. Distribution of the difference between the back- projection Compton scattering angle of incorrect sequence events and the Compton scattering angle required for correct reconstruction.
图 8 $\theta $和${\theta _{{\text{geo}}}}$差异分布 (a) 正确排序事件; (b)混乱排序事件; ${\theta _{{\text{ARM}}}}$分布 (c) 正确排序事件; (d) 混乱排序事件
Fig. 8. Distribution of the difference between $\theta $ and ${\theta _{{\text{geo}}}}$: (a) Correct sequence events; (b) scrambled sequence events. Distribution of ${\theta _{{\text{ARM}}}}$: (c) Correct sequence events; (d) scrambled sequence events.
图 9 综合排序后的分布 (a) $\theta $和${\theta _{{\text{geo}}}}$差异; (b) ${\theta _{{\text{ARM}}}}$分布
Fig. 9. Distribution after sequence reconstruction: (a) Difference between $\theta $ and ${\theta _{{\text{geo}}}}$; (b) ${\theta _{{\text{ARM}}}}$.
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