中国组织工程研究

中国组织工程研究 ›› 2011, Vol. 15 ›› Issue (22): 4090-4093.doi: 10.3969/j.issn.1673-8225.2011.22.024

• 骨与关节图像与影像 bone and joint imaging • 上一篇    下一篇

小波先验在OSL重建算法中的应用

薛  迎，潘晋孝，孔慧华   

  1. 中北大学信息探测与技术处理研究所，山西省太原市  030051
  • 收稿日期:2010-12-22 修回日期:2011-03-22 出版日期:2011-05-28 发布日期:2011-05-28
  • 通讯作者: 潘晋孝，博士生导师，教授，中北大学信息探测与技术处理研究所，山西省太原市 030051 panjx@nuc.edu.cn 并列通讯作者：孔慧华，博士，讲师，中北大学信息探测与技术处理研究所，山西省太原市 030051 fengerkong@nuc.edu.cn
  • 作者简介:薛迎★，女，1985年，山西省运城市人，汉族，中北大学在读硕士，主要从事CT重建算法方面的研究。 xueying112611@163.com
  • 基金资助:

    国家自然科学基金资助项目(60772102，61071193)。山西省自然科学基金资助项目(2010011002-1)。 

Application of wavelet prior in OSL reconstruction algorithm

Xue Ying, Pan Jin-xiao, Kong Hui-hua   

  1. National Key Lab for Electronic Measurement and Technology, North University of China, Taiyuan  030051, Shanxi Province, China
  • Received:2010-12-22 Revised:2011-03-22 Online:2011-05-28 Published:2011-05-28
  • Contact: Pan Jin-xiao, Doctoral supervisor, Professor, National Key Lab for Electronic Measurement and Technology, North University of China, Taiyuan 030051, Shanxi Province, China panjx@nuc.edu.cn Correspondence to: Kong Hui-hua, Doctor, Lecturer, National Key Lab for Electronic Measurement and Technology, North University of China, Taiyuan 030051, Shanxi Province, China fengerkong@nuc.edu.cn
  • About author:Xue Ying★, Studying for master’s degree, National Key Lab for Electronic Measurement and Technology, North University of China, Taiyuan 030051, Shanxi Province, China xueying112611@163.com
  • Supported by:

    the National Natural Science Foundation of China, No. 60772102*, 61071193*; the Natural Science Foundation of Shanxi Province, No. 2010011002-1*

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摘要：

背景：MAP(最大后验)统计重建方法可以在重建过程中引入合适的先验知识达到去除噪声的目的。
目的：根据小波系数的统计特性及能量平衡的原理对高频信息做相应的处理，并将多尺度的小波先验应用到OSL重建算法中以去除噪声。
方法：实验从“变换域”的思想出发，在小波域上根据小波系数的统计特性及能量平衡原理对不同尺度的高频信息做相应的处理，并利用处理后的小波系数进行小波重建。
结果与结论：基于小波先验的OSL算法比ML-EM算法重建的图像与测试模型的误差变小、相关性变大、噪声变少，重建图像变得比较平滑，视觉效果较清楚。

关键词: 小波先验, CT图像重建, OSL重建算法, 高频信息, 噪声

Abstract:

BACKGROUND: MAP (maximum a posteriori) statistical reconstruction methods can introduce appropriate prior knowledge in reconstruction process to remove the noises.
OBJECTIVE: To process the corresponding high frequency information, according to statistic characteristics of wavelet coefficients and energy balance principle, and to apply multi-scale wavelet prior to OSL reconstruction algorithm to remove noises.
METHODS: Most prior information can reduce noise in airspace. From “transform domain”, according to statistic characteristics of wavelet coefficients and energy balance principle of different scales, high frequency information is processed in wavelet domain. And processed wavelet coefficients are applied in wavelet reconstruction as a kind of multi-scale wavelet prior information to remove noises.
RESULTS AND CONCLUSION: The errors and noises of reconstructed images and testing model of OSL algorithm based on wavelet priori information is less than ML-EM algorithm, and correlation greater. Reconstructed images have become smoother, and visual effect is clearer. This shows that wavelet prior, based on wavelet coefficient statistical characteristic and energy balance principle, can effectively reduce the noises in CT reconstruction process.

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