[1]尹朋飞,冯汉升,李实,等.基于非线性估计的CBCT几何标定算法[J].中国医学物理学杂志,2020,37(10):1230-1236.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.004]
　YIN Pengfei,FENG Hansheng,LI Shi,et al.CBCT geometric calibration algorithm based on nonlinear estimation[J].Chinese Journal of Medical Physics,2020,37(10):1230-1236.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.004]
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基于非线性估计的CBCT几何标定算法()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第10期
页码:
1230-1236
栏目:
医学放射物理
出版日期:
2020-10-29

文章信息/Info

Title:
CBCT geometric calibration algorithm based on nonlinear estimation
文章编号:
1005-202X（2020）10-1230-07
作者:
尹朋飞1; 冯汉升2; 李实2; 杨洋2
1.安徽大学电气工程与自动化学院， 安徽 合肥 230601； 2.中国科学院等离子体物理研究所， 安徽 合肥230031
Author(s):
YIN Pengfei1;  FENG Hansheng2;  LI Shi2;  YANG Yang2
1.School?f?lectrical?ngineering?nd?utomation,?nhui?niversity, Hefei 230601, China 2. Institute?f?lasma?hysics,?hinese? Academy?f?ciences, Hefei 230031, China
关键词:
锥形束计算机断层扫描; 几何标定; 非线性优化
Keywords:
Keywords: cone beam computed tomography geometric calibration nonlinear optimization
分类号:
R318；TP391.4
DOI:
DOI:10.3969/j.issn.1005-202X.2020.10.004
文献标志码:
A
摘要:
针对传统的几何标定算法由标定模体位姿误差导致的CBCT成像系统参数标定精度不高的问题，提出一种基于解析几何和非线性优化的CBCT几何标定算法。首先，设计一种插帧追踪的方法，提取特征点的坐标，使得标定模体与投影图像中的特征点实现一一对应。然后，利用投影图片与设计的标定模体之间的空间几何关系，计算相关参数。最后，对检测的特征点进行非线性估计，进一步提高几何参数的计算精度。仿真数据实验表明，本文算法能够较为精确地计算出CBCT成像系统的几何参数，并在标定模体出现位姿偏差时仍然保持较高的计算精度。通过非线性估计模型，本文所提出的算法突破了现有算法标定模体位于等中心点的限制，提高了CBCT成像系统中参数标定的精度。
Abstract:
Abstract: Due to the posture?rror?f calibration phantom, traditional geometric calibration algorithm has a poor accuracy in the parameter calibration of cone beam computed tomography (CBCT) imaging system. In order to solve the above-mentioned problem, a CBCT geometric calibration algorithm based on analytic geometry and nonlinear optimization is proposed. A tracking method based on frame interpolation is firstly designed to extract the coordinates of feature points, thereby achieving the correspondence between the calibration phantom and the feature points in the projected image. Then the relevant parameters are calculated based on the spatial relationship between the projected image and the designed calibration phantom. Finally, the nonlinear estimation of the detected feature points is carried out to further improve the accuracy of geometric parameter calculation. The simulation results verified that the proposed algorithm can accurately calculate the geometric parameters of CBCT imaging system, and maintain a high calculation accuracy even when the posture error is occurred during phantom calibration. Based on the proposed nonlinear estimation model, the proposed method overcomes the limitation of the existing algorithm in which calibration phantom needs to be located at the isocenter and improves the accuracy of parameter calibration in CBCT imaging system.

相似文献/References:

[1]李岩峰,郭晓倩,陈 燕,等.利用CBCT行双侧颞下颌关节对比测量的技术探讨[J].中国医学物理学杂志,2014,31(02):4810.[doi:10.3969/j.issn.1005-202X.2014.02.021]
[2]刘沐然,谭敏慧,张煜.基于深度学习对 CBCT 图像采用多视角投影的牙齿分类[J].中国医学物理学杂志,2025,42(3):313.[doi:10.3969/j.issn.1005-202X.2025.03.005]
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备注/Memo

备注/Memo:
【收稿日期】2020-03-20 【基金项目】中科院合肥物质科学研究院“十三五”规划重点支持项目（KP-2017-24） 【作者简介】尹朋飞，在读硕士，研究方向：图像处理，E-mail: 596712615 @qq.com 【通信作者】冯汉升，博士，研究员，主要从事质子治疗系统研究，E-mail: hsfeng@ipp.ac.cn
更新日期/Last Update: 2020-10-29