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层析成像图像重建算法综述

阎春生 廖延彪 田芊

阎春生, 廖延彪, 田芊. 层析成像图像重建算法综述[J]. 中国光学, 2013, 6(5): 617-632. doi: 10.3788/CO.20130605.0617
引用本文: 阎春生, 廖延彪, 田芊. 层析成像图像重建算法综述[J]. 中国光学, 2013, 6(5): 617-632. doi: 10.3788/CO.20130605.0617
YAN Chun-sheng, LIAO Yan-biao, TIAN Qian. Image reconstruction algorithms of computed tomography[J]. Chinese Optics, 2013, 6(5): 617-632. doi: 10.3788/CO.20130605.0617
Citation: YAN Chun-sheng, LIAO Yan-biao, TIAN Qian. Image reconstruction algorithms of computed tomography[J]. Chinese Optics, 2013, 6(5): 617-632. doi: 10.3788/CO.20130605.0617

层析成像图像重建算法综述

doi: 10.3788/CO.20130605.0617
基金项目: 

光通信、光传感器件与技术科技创新团队资助项目(No.2010R50007);高等学校学科创新引智计划资助项目(No.B07031)

详细信息
    作者简介:

    阎春生(1973-),男,山西文水人,博士,副教授,硕士生导师,1994年、1999年于电子科技大学分别获得学士、硕士学位,2003年于清华大学获得博士学位,主要从事光传感、光层析成像技术及近场光学等方面的研究。E-mail:yancs@zju.edu.cn;廖延彪(1935-),男,江西人,硕士,教授,博士生导师,1957年于武汉大学获得硕士学位,主要从事光纤传感方面的研究。E-mail:lyb-dee@mail.tsinghua.edu.cn;田芊(1946-),男,江苏南通人,教授,博士生导师,1970年于清华大学获得学士学位,主要从事激光技术、光纤传感技术、近场光学等方面的研究。E-mail:tianq@mail.tsinghua.edu.cn

    阎春生(1973-),男,山西文水人,博士,副教授,硕士生导师,1994年、1999年于电子科技大学分别获得学士、硕士学位,2003年于清华大学获得博士学位,主要从事光传感、光层析成像技术及近场光学等方面的研究。E-mail:yancs@zju.edu.cn;廖延彪(1935-),男,江西人,硕士,教授,博士生导师,1957年于武汉大学获得硕士学位,主要从事光纤传感方面的研究。E-mail:lyb-dee@mail.tsinghua.edu.cn;田芊(1946-),男,江苏南通人,教授,博士生导师,1970年于清华大学获得学士学位,主要从事激光技术、光纤传感技术、近场光学等方面的研究。E-mail:tianq@mail.tsinghua.edu.cn

    阎春生(1973-),男,山西文水人,博士,副教授,硕士生导师,1994年、1999年于电子科技大学分别获得学士、硕士学位,2003年于清华大学获得博士学位,主要从事光传感、光层析成像技术及近场光学等方面的研究。E-mail:yancs@zju.edu.cn;廖延彪(1935-),男,江西人,硕士,教授,博士生导师,1957年于武汉大学获得硕士学位,主要从事光纤传感方面的研究。E-mail:lyb-dee@mail.tsinghua.edu.cn;田芊(1946-),男,江苏南通人,教授,博士生导师,1970年于清华大学获得学士学位,主要从事激光技术、光纤传感技术、近场光学等方面的研究。E-mail:tianq@mail.tsinghua.edu.cn

    通讯作者:

    阎春生

  • 中图分类号: R445;TP391

Image reconstruction algorithms of computed tomography

  • 摘要: 介绍了层析成像技术的图像重建算法,并从正向问题数学模型的简化和反向问题数学模型的映射结构的角度比较了各种算法的特点和优劣。研究表明:用本质是线性算法的各种变换方法重建图像存在严重失真,而卷积滤波的引入可以使变换方法的重建效果有所改善;基于导数搜索的迭代算法对初始值依赖性强、收敛速度慢并且容易陷入局部最优解;基于Fourier变换的方法具有本质的局限性;小波变换则可以同时刻画图像时域和频域的细节特征;有限元法通过重建对象像素的智能划分可以简化正问题的复杂性;而具有物理背景的蒙特卡罗法、模拟退火法、遗传算法、粒子滤波法及神经网络法更适合于复杂且非线性的图像重建;智能化、仿生化、并行化以及各种算法的融合是层析成像图像重建算法的发展趋势。
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  • 收稿日期:  2013-07-21
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