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基于U型生成对抗网络的编码孔径CT成像方法

王志腾 冒添逸 张昕 朱书进 朱建建 戴修斌

王志腾, 冒添逸, 张昕, 等. 基于U型生成对抗网络的编码孔径CT成像方法[J]. CT理论与应用研究, 2022, 31(3): 317-327. DOI: 10.15953/j.ctta.2021.070
引用本文: 王志腾, 冒添逸, 张昕, 等. 基于U型生成对抗网络的编码孔径CT成像方法[J]. CT理论与应用研究, 2022, 31(3): 317-327. DOI: 10.15953/j.ctta.2021.070
WANG Z T, MAO T Y, ZHANG X, et al. Coded aperture computed tomography via generative adversarial U-net[J]. CT Theory and Applications, 2022, 31(3): 317-327. DOI: 10.15953/j.ctta.2021.070. (in Chinese)
Citation: WANG Z T, MAO T Y, ZHANG X, et al. Coded aperture computed tomography via generative adversarial U-net[J]. CT Theory and Applications, 2022, 31(3): 317-327. DOI: 10.15953/j.ctta.2021.070. (in Chinese)

基于U型生成对抗网络的编码孔径CT成像方法

doi: 10.15953/j.ctta.2021.070
基金项目: 国家自然科学基金(基于编码孔径的非扫描四维CT成像方法(62005128));江苏省自然科学基金(基于多尺度细粒度网络和二值自编码模型的病理图像快速检索研究(BK20200745));江苏省高等学校自然科学研究(基于动态变尺度栈式二值自编码的病理图像实时检索研究(20KJB510022))。
详细信息
    作者简介:

    王志腾:男,南京邮电大学电子信息专业硕士研究生,主要从事CT理论与应用研究,E-mail:1220013724@njupt.edu.cn

    戴修斌:男,南京邮电大学地理与生物信息学院副教授、硕士生导师,主要从事CT理论与应用研究,E-mail:daixb@njupt.edu.cn

  • 中图分类号: TP  391.41;TP  183

Coded Aperture Computed Tomography Via Generative Adversarial U-net

  • 摘要: 针对编码孔径CT成像非连续稀疏采样只能通过代数类迭代重建算法的缺点,本文提出一种基于U型生成对抗网络的编码孔径CT成像方法。通过构建基于U型生成对抗网络的非连续稀疏投影的动态博弈模型,结合联合损失函数,预测正弦图的结构性缺失,实现编码孔径CT成像分析类(非迭代)快速重建。实验结果表明,在辐射剂量降低95% 的条件下,基于U型生成对抗网络的编码孔径CT成像方法实现了峰值信噪比大于30 dB @ 256×256的高质量重建。相比于目前最先进的编码孔径CT成像方法,其重建时间降低了约两个数量级。

     

  • 图  1  编码孔径CT成像光学几何结构示意图

    Figure  1.  The setup of coded aperture computed tomography

    图  2  正弦图

    Figure  2.  Sinogram

    图  3  本文提出的非连续性投影数据训练和测试框架

    Figure  3.  The framework of training and testing for discrete projection data

    图  4  U型生成对抗网络结构图

    Figure  4.  Generative Adversarial U-Net for coded aperture computed tomography

    图  5  编码掩膜板透过率为20%,训练次数为115个epoch的结果图

    Figure  5.  The results for coded apertures at 20% transmittance

    图  6  编码掩膜板透过率为25% 时基于U型生成对抗网络的编码孔径CT成像结果

    Figure  6.  The reconstructed images for coded apertures computed tomography at 25% transmittance

    图  7  编码掩膜板透过率为5%、15% 和25%时基于U型生成对抗网络的编码孔径CT成像结果

    Figure  7.  The reconstructed images for coded apertures computed tomography at 5%, 15% and 25% transmittance, respectively

    表  1  不同编码掩膜板透过率下,测试集中预测的正弦图和CT重建图像的平均值

    Table  1.   The average results of sonograms and CT reconstructions at different transmission rates

    测试数据集图像质量评价指标编码掩膜板透过率
    5%10%15%20%25%
    预测的正弦图 PSNR/dB39.141.640.942.643.8
    SSIM0.980.970.980.990.98
    CT重建图像 PSNR/dB33.732.033.535.333.6
    SSIM0.880.880.890.910.90
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-12-20
  • 录用日期:  2022-02-25
  • 网络出版日期:  2022-03-10
  • 刊出日期:  2022-05-23

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