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极稀疏投影数据的CT图像重建

武丽君 孙丰荣 杨江飞 于倩蕾 贺芳芳

武丽君, 孙丰荣, 杨江飞, 等 . 极稀疏投影数据的CT图像重建[J]. 北京航空航天大学学报, 2020, 46(12): 2366-2373. doi: 10.13700/j.bh.1001-5965.2019.0613
引用本文: 武丽君, 孙丰荣, 杨江飞, 等 . 极稀疏投影数据的CT图像重建[J]. 北京航空航天大学学报, 2020, 46(12): 2366-2373. doi: 10.13700/j.bh.1001-5965.2019.0613
WU Lijun, SUN Fengrong, YANG Jiangfei, et al. CT image reconstruction from ultra-sparse projection data[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(12): 2366-2373. doi: 10.13700/j.bh.1001-5965.2019.0613(in Chinese)
Citation: WU Lijun, SUN Fengrong, YANG Jiangfei, et al. CT image reconstruction from ultra-sparse projection data[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(12): 2366-2373. doi: 10.13700/j.bh.1001-5965.2019.0613(in Chinese)

极稀疏投影数据的CT图像重建

doi: 10.13700/j.bh.1001-5965.2019.0613
基金项目: 

国家自然科学基金 81671703

山东省自然科学基金 ZR2019MF048

详细信息
    作者简介:

    武丽君  女, 硕士研究生。主要研究方向:生物医学信号与信息处理

    孙丰荣  男, 博士, 教授。主要研究方向:CT图像重建、基于人工智能的医学影像分析与诊断

    通讯作者:

    孙丰荣, E-mail:sunfr_journal@163.com

  • 中图分类号: TP391;TN911.73

CT image reconstruction from ultra-sparse projection data

Funds: 

National Natural Science Foundation of China 81671703

Nalural Seience Foundation of Shandong Province ZR2019MF048

More Information
  • 摘要:

    从稀疏投影数据足够精确地重建断层图像,从而能够在显著降低计算机断层成像(CT)检查X-射线辐射剂量的前提下,提供充分适宜影像学临床诊断需求的重建图像。针对圆周扫描扇束投影的二维CT图像重建,提出了投影驱动的系统模型,并将CT迭代图像重建与压缩感知(CS)理论相结合,设计了一种CT迭代图像重建算法,且将算法扩展到圆周扫描锥束投影的三维CT图像重建。仿真实验结果表明:在极稀疏投影数据的条件下([0,2π)范围内扇束/锥束扫描不超过20个投影角度),算法数值精度高,计算复杂度低,内存开销少,有很强的工程实用性。

     

  • 图 1  二维扇束投影示意图与细节图

    Figure 1.  Schematic diagram and detailed diagram of two-dimensional fan-beam projection

    图 2  正/反投影矩阵元素示意图

    Figure 2.  Schematic diagram of matrix elements of forward/backward projection

    图 3  循环2

    Figure 3.  Loop 2

    图 4  圆周CT扫描系统结构示意图

    Figure 4.  Schematic diagram of circular CT scanning system

    图 5  Shepp-Logan模型和重建图像及其中心行像素值比较

    Figure 5.  Shepp-Logan model and reconstructed images, as well as comparison of pixel values of center row between them

    图 6  各个投影角度数下不同算法的重建图像质量对比

    Figure 6.  Comparison of reconstructed image quality of different algorithms under various projection angles

    图 7  Shepp-Logan模型透视图和重建图像(第125层和128层)

    Figure 7.  Perspective of Shepp-Logan model and reconstructed images(125th and 128th layers)

    表  1  CT扫描参数和仿真模型信息

    Table  1.   CT scanning parameters and simulation model information

    仿真参数 二维扇束 三维锥束
    检测器类型 平板检测器 平板检测器
    行/列检测器数 512 256
    行/列检测器中心 255.5 127.5
    行/列检测器间距/mm 1.0 1.0
    光源到旋转中心距离/mm 640 640
    旋转中心到检测器中心距离/mm 640 640
    仿真模型 二维Shepp-Logan 三维Shepp-Logan模型
    模型尺寸:512×512 模型尺寸:256×256×256
    模型像素尺寸:0.5mm×0.5mm 体素尺寸:0.5mm×0.5mm×0.5mm
    下载: 导出CSV

    表  2  各个投影角度数下不同算法的重建结果

    Table  2.   Reconstruction results of different algorithms under various projection angles

    重建算法 NRMSE PSNR UQI 重建时间/s
    FBP 0.9641 12.4663 0.5222 4.094
    ART-TV 0.3387 21.5526 0.9181 69.585
    CSVD 0.1958 26.3113 0.9734 32.997
    下载: 导出CSV

    表  3  CSVD算法重建图像质量评价

    Table  3.   Quality evaluation of reconstructed images using CSVD algorithm

    质量评价指标 20个投影角度 18个投影角度
    NRMSE 0.2887 0.2980
    PSNR 22.9883 22.7137
    UQI 0.9406 0.9362
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-12-05
  • 录用日期:  2020-06-12
  • 刊出日期:  2020-12-20

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