ISSN 1004-4140
CN 11-3017/P
| Citation: |
CAO J S, LI B L. Analysis of Accuracy Related Factors in Photon Counting X-ray CT Energy Imaging[J]. CT Theory and Applications, 2025, 34(2): 255-262. DOI: 10.15953/j.ctta.2024.254. (in Chinese).
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Multi-energy spectrum imaging with photon counting detectors has become the focus of X-ray imaging. In this study, the Geant4 simulation software was used to generate the energy spectrum of the ray source, obtaining high-low energy spectra of different ranges by setting different detector energy resolutions and changing the energy threshold. High-low energy projection data of scan objects were obtained for dual-energy reconstruction. The standard deviation of the effective atomic number and electron density under each group were compared. The results show that the higher the energy resolution and the greater the difference between high and low energy spectra, the better is the imaging quality. The energy threshold influenced the imaging accuracy when the spectrum overlap ratio was changed. When the spectrum overlap became smaller and the spectral width became narrower, noise increased, making it necessary to balance the relationship between spectrum overlap and noise to achieve better imaging results.
| [1] |
陈志强, 张丽, 金鑫. X射线安全检查技术研究新进展[J]. 科学通报, 2017, 62(13): 1350-1364. DOI: 10.1360/N972016-00698.
CHEN Z Q, ZHANG I, JIN X. New progress in X-ray safety inspection technology[J]. Chinese Science Bulletin, 2017, 62(13): 1350-1364. DOI: 10.1360/N972016-00698. (in Chinese).
|
| [2] |
ALVAREZ R E. Extraction of energy-dependent information in radiography[D]. California: Stanford University, 1976.
|
| [3] |
郝佳, 张丽, 陈志强, 等. 多能谱X射线成像技术及其在CT中的应用[J]. CT理论与应用研究, 2011, 20(1): 141-150.
HAO J, ZHANG L, CHEN Z Q, et al. Multi-energy X-ray imaging technique and its application in computed tomography[J]. CT Theory and Applications, 2011, 20(1): 141-150. (in Chinese).
|
| [4] |
邸云霞, 孔慧华, 牛晓伟. 基于主成分分析的多能谱CT图像分析方法研究[J]. CT理论与应用研究, 2022, 31(6): 749-760. DOI: 10.15953/j.ctta.2022.077.
DI Y X, KONG H H, NIU X W. Research on image analysis method of spectral CT based on principal component analysis[J]. CT Theory and Applications, 2022, 31(6): 749-760. DOI: 10.15953/j.ctta.2022.077. (in Chinese).
|
| [5] |
余子丽. 多能光子技术X-CT的图像重建方法研究[D]. 南京: 南京航空航天大学, 2016.
YU Z L. A research on image reconstruction method for multi-energy photon counting X-CT[D]. Nangjing: Nanjing University of Aeronautics and Astronautics, 2016. (in Chinese).
|
| [6] |
张煜林. 基于光子计数探测器多能谱CT重建算法及应用研究[D]. 太原: 中北大学, 2017.
ZHANG Y L. Multi-spectral CT reconstruction algorithm based on photon count detector and its application[D]. Taiyuan: North University of China, 2017. (in Chinese).
|
| [7] |
HATEM ALKADHI, ANDRÉ EULER, DAVID MAINTZ, et al. Spectral Imaging[M]. Switzerland: Springer, 2022.
|
| [8] |
邸云霞. 基于能谱CT的材料分解方法研究[D]. 太原: 中北大学, 2023.
DI Y X. Study on material decomposition method based on energy spectrum CT[D]. Taiyuan: North University of China, 2023. (in Chinese).
|
| [9] |
AVINASH C K, MALCOLM S. Principles of computerized tomographic imaging[M]. IEEE Press, 1988.
|
| [10] |
张斯龙. 提高半导体探测器能量分辨率的信号获取方法研究[D]. 湘潭: 湘潭大学, 2021.
ZHANG S L. Research on signal acquisition methodto improve high energy resolution of semiconductor detector[D]. Xiangtan: Xiangtan University, 2021. (in Chinese).
|
| [11] |
OpenGATE Collaboration. Introduction of GATE [EB/OL]. https://opengate.readthedocs.io/en/latest/index.html, 2024.
|
| [12] |
寇松峰, 陈钱, 顾国华, 等. 光子计数成像研究[J]. 应用光学, 2008, 29(5): 675-678. DOI: 10.3969/j.issn.1002-2082.2008.05.003.
KOU S F, CHEN Q, GU G H, et al. Research on photon counting imaging technology[J]. Journal of Applied Optics, 2008, 29(5): 675-678. DOI: 10.3969/j.issn.1002-2082.2008.05.003. (in Chinese).
|
| [13] |
陈松懋, 郝伟, 苏秀琴, 等. 光子计数成像算法的研究进展[J]. 激光与光电子学进展, 2021, 58(18): 1-16. DOI: 10.3788/LOP202158.1811010.
CHEN S M, HAO W, SU X Q, et al. Research progress on photon counting imaging algorithms[J]. Laser & Optoelectronics Progress, 2021, 58(18): 1-16. DOI: 10.3788/LOP202158.1811010. (in Chinese).
|
| [14] |
李保磊, 张萍宇, 李斌, 等. X射线双能计算机层析成像投影分解的优化迭代方法[J]. 光学学报, 2017, 37(10): 1-10. DOI: 10.3788/AOS201737.1034001.
LI B L, ZHANG P Y, LI B, et al. Optimized iterative method for projection decompositi on of X-ray dual-energy computed tomography[J]. Acta Optica Sinica, 2017, 37(10): 1-10. DOI:10.3788/AOS201737.1034001. (in Chinese).
|
| [15] |
庄天戈. CT原理与算法[M]. 上海: 上海交通大学出版社, 1992.
ZHUANG T G. CT principle and algorithm[M]. Shanghai: Shanghai Jiaotong University Press, 1992. (in Chinese).
|
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