ISSN 1004-4140
CN 11-3017/P

基于新的非局部先验模型的Bayesian低剂量CT重建算法

姜盛杰

姜盛杰. 基于新的非局部先验模型的Bayesian低剂量CT重建算法[J]. CT理论与应用研究, 2014, 23(3): 395-402.
引用本文: 姜盛杰. 基于新的非局部先验模型的Bayesian低剂量CT重建算法[J]. CT理论与应用研究, 2014, 23(3): 395-402.
JIANG Sheng-jie. Bayesian Reconstruction Algorithm for Low-dose CT Based on New Nonlocal Prior Model[J]. CT Theory and Applications, 2014, 23(3): 395-402.
Citation: JIANG Sheng-jie. Bayesian Reconstruction Algorithm for Low-dose CT Based on New Nonlocal Prior Model[J]. CT Theory and Applications, 2014, 23(3): 395-402.

基于新的非局部先验模型的Bayesian低剂量CT重建算法

详细信息
    作者简介:

    姜盛杰(1956-),男,丹东奥龙射线仪器集团有限公司高级工程师,主要从事技术开发,系统设计等工作,Tel:13841518919,E-mail:jsj8919@sina.com

    通讯作者:

    姜盛杰(1956-),男,丹东奥龙射线仪器集团有限公司高级工程师,主要从事技术开发,系统设计等工作,Tel:13841518919,E-mail:jsj8919@sina.com

  • 中图分类号: TP301.6

Bayesian Reconstruction Algorithm for Low-dose CT Based on New Nonlocal Prior Model

  • 摘要: 为了改善低剂量CT重建图像质量,在传统非局部先验的基础上,提出了一种基于投影对称性的改进非局部先验模型。基于该先验模型构造了一种贝叶斯(Bayesian)重建算法,并将其应用到低剂量CT投影数据降噪中,通过滤波反投影算法重建出图像。仿真实验结果表明,本文所提出的算法较基于传统先验模型的重建算法,能在去除噪声与保持边缘之间取得较好的平衡。
    Abstract: In order to improve the quality of low-dose CT reconstructed image, this study proposes a projection symmetry-based modified nonlocal prior model based on the traditional nonlocal prior model. Then, a Bayesian reconstruction algorithm is built combined with this prior model, and it is applied to the noise removal of the low-dose CT projection data. The reconstructed images are obtained by the filtered back-projection(FBP)algorithm. The results of simulated experiment show the proposed algorithm, compared with the algorithms based on the traditional priors, can achieve a superior balance between suppressing noise and preserving edges.
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出版历程
  • 收稿日期:  2014-01-01
  • 网络出版日期:  2022-12-09

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