电子学报 ›› 2012, Vol. 40 ›› Issue (1): 27-34.DOI: 10.3969/j.issn.0372-2112.2012.01.005

• 学术论文 • 上一篇    下一篇

基于EM算法的低剂量CT图像去噪

张元科1, 张军英2, 卢虹冰3   

  1. 1. 曲阜师范大学计算机学院,山东日照 276826;2. 西安电子科技大学计算机学院,陕西西安 710071;3. 第四军医大学生物医学工程系,陕西西安 710032
  • 收稿日期:2010-03-29 修回日期:2011-09-06 出版日期:2012-01-25
    • 基金资助:
    • 国家自然科学基金 (No.61070137); 国家科技支撑计划 (No.2011BAI12B03); 国家自然科学基金重点项目 (No.60933009); 山东省自然科学基金 (No.ZR2009GM009)

Noise Reduction of Low-Dose CT Sinograms Based on EM Algorithm

ZHANG Yuan-ke1, ZHANG Jun-ying2, LU Hong-bing3   

  1. 1. School of Computer Science,Qufu Normal University,Rizhao,Shandong 276826,China;2. School of Computer Science and Technology,Xidian University,Xi'an,Shaanxi 710071,China;3. Faculty of Biomedical Engineering,Fourth Military Medical University,Xi'an,Shaanxi 710032,China
  • Received:2010-03-29 Revised:2011-09-06 Online:2012-01-25 Published:2012-01-25

摘要: 提高低剂量CT图像的信噪比是使其获得有效临床应用的关键.文中针对低剂量CT投影数据极低信噪比特性以及投影数据噪声所特有的非平稳高斯特性,提出采用EM(Expectation-Maximization)算法通过求解图像后验概率的条件期望值最大的方法达到图像复原目的,同时在算法中实现了图像模型参数的估计,并且引入Gibbs采样技术,很好的解决了算法计算问题.计算机仿真及真实投影数据的实验表明,本文算法无论从复原图像的可视化效果上还是从噪声-分辨率关系的定量分析上,都具有一定优势.

关键词: 低剂量CT, 图像去噪, 参数估计, EM算法

Abstract: Improving of the SNR of the low-dose CT image is a crucial issue for the low-dose CT application.In this paper,we employed an EM (expectation-maximization) scheme to restore the sinogram by the maximum a conditional expectation of the posteriori estimation,based on the special statistical property of low-dose CT sinogram,i.e.,the extremely low SNR and the non-stationary noise property of the sinogram data.At the same time,parameters of the statistical model were estimated in the EM scheme.In addition,a Gibbs sampler was used to solve the computation problem.The effectiveness of the proposed algorithm was validated by both computer simulations and experimental studies.The gain of the proposed approach over other methods was quantified by noise-resolution tradeoff curves.

Key words: low-dose CT, noise reduction, parameter estimation, EM algorithm

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