基于Geant4/GATE平台模拟移动式锥形束CT成像

doi:10.13491/j.issn.1004-714X.2021.06.010

2021, Vol. 30

Issue (6): 706-709,719 DOI: 10.13491/j.issn.1004-714X.2021.06.010

Radiation Monitoring/Original Articles

Current Issue | Archive | Adv Search

Simulation of mobile cone-beam CT imaging based on the Geant4/GATE platform

MING Xin¹, WANG Yongjian¹, ZHAI Hezheng^2,3, YANG Chengwen⁴, MENG Huipeng⁵, YANG Jian⁶, BO Wenzhu⁶

1. Tianjin Medical University, Tianjin 300203 China;
2. Tianjin University, Tianjin 300072 China;
3. Institute of Radiation Medicine, Chinese Academy of Medical Sciences, Tianjin 300192 China;
4. Tianjin Medical University Cancer Hospital, Tianjin 300060 China;
5. Characteristic Medical Center of PAP, Tianjin 300162 China;
6. Tianjin Jinxi Medical Equipment Co., Ltd., Tianjin 300385 China

Abstract
Figure/Table
References
Related Citation (8)

Download: PDF (1068 KB) HTML ( )
Export: BibTeX | EndNote (RIS)

Abstract Objective To simulate mobile cone-beam computed tomography (CBCT) imaging based on the Geant4/GATE platform and to explore the optimization method to improve image quality. Methods Mobile CBCT imaging was simulated based on the Geant4/GATE platform of Monte Carlo algorithm to establish the models of X-ray source, flat panel detector, and phantom, and projection data of CBCT were obtained. Three image reconstruction algorithms (FDK, SART, and EM) were used for image reconstruction of the designed digital phantom with the projection data at two X-ray energy levels. Results FDK was the fastest algorithm, SART had high contrast quality, low artifacts, and high image quality; EM had minimum noise but fuzzy boundaries of inserts of different density. With the SART algorithm, the images reconstructed at 70 kV X-ray were scatters, while the images reconstructed at 140 kV X-ray had high quality. Conclusion Simulation of mobile CBCT based on the Geant4/GATE platform can reconstruct 3D images of the digital phantom, which provides a theoretical basis for further research on image quality optimization and quality control of mobile CBCT.

Key words： CBCT Image Reconstruction Scattering Correction

Received: 18 July 2021

PACS:

R816

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	MING Xin
	WANG Yongjian
	ZHAI Hezheng
	YANG Chengwen
	MENG Huipeng
	YANG Jian
	BO Wenzhu

Cite this article:

MING Xin,WANG Yongjian,ZHAI Hezheng, et al. Simulation of mobile cone-beam CT imaging based on the Geant4/GATE platform[J]. , 2021, 30(6): 706-709,719.

URL:

http://www.zgfsws.com/EN/10.13491/j.issn.1004-714X.2021.06.010 OR http://www.zgfsws.com/EN/Y2021/V30/I6/706

[1] Evans MRB, White P, Cowley P, et al. Revolution in acute ischaemic stroke care: a practical guide to mechanical thrombectomy[J]. Pract Neurol, 2017, 17(4): 252-265. DOI: 10.1136/practneurol-2017-001685
[2] 刘伟, 张倩, 陈思运, 等. 移动CT相对于传统CT存在的优势[J]. 生物医学工程与临床,2020,24(3):343-345. DOI: 10.13339/j.cnki.sglc.20200414.012
Liu W, Zhang Q, Chen SY, et al. Advantages of mobile CT over traditional CT[J]. Biomed Eng Clin Med, 2020, 24(3): 343-345. DOI: 10.13339/j.cnki.sglc.20200414.012
[3] 姜庆寰, 尉可道, 王建超, 等. 锥形束CT(CBCT)在医学实践中应用的进展[J]. 中国辐射卫生,2017,26(3):316-321. DOI: 10.13491/j.cnki.issn.1004-714X.2017.03.021
Jiang QH, Wei KD, Wang JC, et al. Progress of the application of cone beam computed tomography (CBCT) in medical practice[J]. Chin J Radiol Health, 2017, 26(3): 316-321. DOI: 10.13491/j.cnki.issn.1004-714X.2017.03.021
[4] 张伟欣. 基于MSCT及CBCT技术的便携式移动CT临床应用分析[J]. 生物医学工程学进展,2021,42(2):100-102. DOI: 10.3969/j.issn.1674-1242.2021.02.009
Zhang WX. Clinical application of portable mobile CT based on MSCT and CBCT technology[J]. Prog Biomed Eng, 2021, 42(2): 100-102. DOI: 10.3969/j.issn.1674-1242.2021.02.009
[5] 孟慧鹏, 王克强, 付娟, 等. 一种基于Monte Carlo模拟的锥形束CT图像散射校准方法[J]. 辐射研究与辐射工艺学报,2019,37(4):25-32. DOI: 10.11889/j.1000-3436.2019.rrj.37.040303
Meng HP, Wang KQ, Fu J, et al. Method of core-beam CT imaging scatter correction based on Monte Carlo simulations[J]. J Radiat Res Radiat Process, 2019, 37(4): 25-32. DOI: 10.11889/j.1000-3436.2019.rrj.37.040303
[6] Zhang YM, Chen YS, Zhong AN, et al. Scatter correction based on adaptive photon path-based Monte Carlo simulation method in Multi-GPU platform[J]. Comput Methods Programs Biomed, 2020, 194: 105487. DOI: 10.1016/j.cmpb.2020.105487
[7] Skaarup M, Edmund JM, Dorn S, et al. Dual-energy material decomposition for cone-beam computed tomography in image-guided radiotherapy[J]. Acta Oncol, 2019, 58(10): 1483-1488. DOI: 10.1080/0284186X.2019.1629010
[8] 中华人民共和国国家卫生健康委员会. WS 76—2020 医用X射线诊断设备质量控制检测规范[S]. 北京: 中国标准出版社, 2020.
National Health Commission of the People’s Republic of China. WS 76—2020 Specification for testing of quality control in medical X-ray diagnostic equipment[S]. Beijing: Standards Press of China, 2020.