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

ZHANG Yuan-ke; ZHANG Jun-ying; LU Hong-bing

doi:10.3969/j.issn.0372-2112.2012.01.005

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

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- Noise Reduction of Low-Dose CT Sinograms Based on EM Algorithm
- Acta Electronica Sinica Vol. 40, Issue 1, Pages: 27-34(2012)
- 作者机构：
  
  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
  4. 曲阜师范大学计算机学院山东日照,276826
  5. 西安电子科技大学计算机学院陕西西安,710071
  6. 第四军医大学生物医学工程系陕西西安,710032
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2012.01.005
  CLC： TP391
- Published：2012
- 稿件说明：
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ZHANG Yuan-ke, ZHANG Jun-ying, LU Hong-bing. Noise Reduction of Low-Dose CT Sinograms Based on EM Algorithm[J]. Acta Electronica Sinica, 2012, 40(1): 27-34.
DOI：

ZHANG Yuan-ke, ZHANG Jun-ying, LU Hong-bing. Noise Reduction of Low-Dose CT Sinograms Based on EM Algorithm[J]. Acta Electronica Sinica, 2012, 40(1): 27-34. DOI： 10.3969/j.issn.0372-2112.2012.01.005.

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.

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.

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Related Institution

School of Electrical Engineering and Automation, Wuhan University

National Key Laboratory of Electromagnetic Energy, Naval University of Engineering

School of Electronic Information and Communications, Huazhong University of Science and Technology

（武汉大学软件工程国家重点实验室, ）

Institute of Medical Information and Technology,School of Biomedical Engineering,Southern Medical University

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