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程丽君, 孙正, 孙美晨, 侯英飒

BECK A, TEBOULLE M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems[J]. SIAM Journal on Imaging Sciences, 2009, 2(1): 183-202. (查阅网上资料, 本条与第21条文献重复, 请确认). doi: 10.37188/CO.2023-0114
引用本文: BECK A, TEBOULLE M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems[J]. SIAM Journal on Imaging Sciences, 2009, 21): 183-202. (查阅网上资料, 本条与第21条文献重复, 请确认). doi: 10.37188/CO.2023-0114
CHENG Li-jun, SUN Zheng, SUN Mei-chen, HOU Ying-sa. 365彩票官网[J]. Chinese Optics. doi: 10.37188/CO.2023-0114
Citation: CHENG Li-jun, SUN Zheng, SUN Mei-chen, HOU Ying-sa. 365彩票官网[J]. Chinese Optics. doi: 10.37188/CO.2023-0114

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doi: 10.37188/CO.2023-0114
基金项目:国家自然科学基金资助项目(No. 62071181)
详细信息
    作者简介:

    程丽君(1998—),女,山东菏泽人,硕士研究生,2021年于山东第一医科大学获得工学学士学位,主要从事光声图像重建方面的研究。E-mail:[email protected]

    孙正(1977—),女,河北保定人,博士,教授,硕士生导师,1999年、2004年于天津大学分别获得工学学士和工学博士学位,主要从事多模态成像技术、图像重建和反问题求解等的研究。E-mail:[email protected]

    孙美晨(1996—),女,河北保定人,硕士研究生,2019年于华北电力大学科技学院获得工学学士学位,2023年于华北电力大学获得工学硕士学位,主要从事图像重建等的研究。E-mail:[email protected]

    侯英飒:候英飒(1997—),女,河北保定人,硕士研究生,2020年于河北经贸大学获得工学学士学位,2023年于华北电力大学获得工学硕士学位,主要从事光声图像重建技术等的研究。E-mail:[email protected]

  • 中图分类号:TP391

365彩票官网

Funds:Supported by National Natural Science Foundation of China (No. 62071181)
More Information
  • 摘要:

    为了解决在光声层析成像(photo acoustic tomography,PAT)中,由于不均匀光通量分布、组织复杂的光学和声学特性以及超声探测器的非理想特性等因素所致的重建图像质量下降的问题。本文提出一种PAT图像重建方法,建立考虑不均匀光通量、非定常声速、超声探测器的空间脉冲响应和电脉冲响应、有限角度扫描和稀疏采样等因素的前向成像模型,通过交替优化求解成像模型的逆问题,实现光吸收能量分布图和声速分布图的同时重建。仿真、仿体和在体实验结果表明,与反投影法、时间反演法和短滞后空间相干法相比,该方法重建图像的结构相似度和峰值信噪比可分别提高约83%、56%、22%和80%、68%、58%。与传统方法相比,对非理想成像场景采用该方法重建的图像质量有显著提高。

  • 图 1 数值仿体的横截面几何结构

    Figure 1. Cross-sectional geometry of numerical phantoms

    图 2 仿体的实物照片

    Figure 2. Physical photo of phantoms

    图 3 活体小鼠光声层析成像实验系统示意图

    Figure 3. Schematic diagram of PAT experimental setup for in vivo mice

    图 4 根据全角度密集采样的仿真光声信号重建的图像及其评价指标 (a) 标准图像和重建图像;(b)评价指标

    Figure 4. Reconstructed distribution maps and their evaluation metrics based on simulated photoacoustic signals that are densely-sampled and collected at a full-angle (a) standard and reconstructed images; (b) evaluation metrics

    图 5 根据有限角度稀疏采样仿真光声信号重建的光吸收能量分布图及其评价指标 (a) 重建图像;(b) 评价指标

    Figure 5. Reconstructed light absorption energy distribution maps and their evaluation metrics based on limited-view sparse sampling simulated data. (a) reconstructed images; (b) evaluation metrics.

    图 6 仿体图像重建结果及评价指标 (a) 光吸收能量分布图;(b) 声速分布图;(c) 评价指标

    Figure 6. Reconstructed distribution maps and their evaluation metrics of phantoms. (a) AOED distribution map; (b) SoS distribution map; (c) evaluation metrics.

    图 7 小鼠胸腹切片图像重建结果及评价指标 (a) 光吸收能量分布图;(b) 声速分布图;(c) 光吸收能量分布图评价指标

    Figure 7. Reconstructed thoracic and abdominal slice images of in vivo mice and evaluation metrics. (a) AOED distribution map; (b) SoS distribution map; (c) evaluation metrics of distribution map.

    图 8 采用不同迭代初始值时的重建图像和迭代次数 (a) 重建图像;(b) 重建模型1中不同位置处的AOED所需的迭代次数

    Figure 8. Reconstructed distribution maps using different iterative initial values and the number of iterations. (a) reconstructed images; (b) number of iterations required for AOED at different locations in the reconstructed model 1

    图 9 采用不同优化算法重建的AOED分布图及其评价指标 (a) 重建图像;(b) 评价指标

    Figure 9. Reconstructed distribution maps and their evaluation metrics of AOED map reconstructed using different optimization algorithms. (a) reconstructed images; (b) evaluation metrics.

    图 10 不同固定声速条件下,根据仿真光声信号重建的AOED分布图和评价指标 (a) 重建图像;(b) 评价指标

    Figure 10. Reconstructed AOED distribution map and evaluation metrics based on simulated photoacoustic signals at different fixed sound speeds. (a) reconstructed images; (b) evaluation metrics.

    图 11 优化光通量对重建图像质量的影响 (a) 重建的AOED图像;(b) 评价指标

    Figure 11. Effect of optimized luminous flux on reconstructed image quality (a) reconstructed AOED image; (b) evaluation metrics.

    图 12 采用不同的考虑超声探测器响应的方法重建的光吸收能量分布图和评价指标 (a) 重建图像;(b) 评价指标

    Figure 12. Reconstructed AOED distribution maps and their evaluation metrics using different methods of considering ultrasonic detector response. (a) reconstructed images; (b) evaluation metrics.

    表  1 数值仿真模型的组织特性参数

    Table  1. Tissue property parameters of numerical phantoms

    组织
    名称
    组织
    成分
    折射率 吸收系数
    (cm‒1)
    散射系数
    (cm‒1)
    各向异
    性因子
    声速
    (m/s)
    密度
    (kg/L)
    心脏 肌肉组织 1.37 0.78 132 0.96 1580 1.060
    肌肉组织 1.37 0.72 114 0.95 1561 1.043
    结缔组织 1.36 0.76 205 0.90 1560 1.050
    肝脏 肌肉组织 1.37 0.75 103 0.91 1595 1.060
    胸骨 钙质 1.37 0.05 150 0.96 1580 1.050
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