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生物光声层析成像中不均匀和不稳定照明解决方法

孟琪 孙正

孟琪, 孙正. 生物光声层析成像中不均匀和不稳定照明解决方法[J]. 中国光学, 2021, 14(2): 307-319. doi: 10.37188/CO.2020-0142
引用本文: 孟琪, 孙正. 生物光声层析成像中不均匀和不稳定照明解决方法[J]. 中国光学, 2021, 14(2): 307-319. doi: 10.37188/CO.2020-0142
MENG Qi, SUN Zheng. Solutions to inhomogeneous and unstable illumination in biological photoacoustic tomography[J]. Chinese Optics, 2021, 14(2): 307-319. doi: 10.37188/CO.2020-0142
Citation: MENG Qi, SUN Zheng. Solutions to inhomogeneous and unstable illumination in biological photoacoustic tomography[J]. Chinese Optics, 2021, 14(2): 307-319. doi: 10.37188/CO.2020-0142

生物光声层析成像中不均匀和不稳定照明解决方法

doi: 10.37188/CO.2020-0142
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:

    孟琪:孟 琪(1995—),女,山东临沂人,硕士研究生,2018年于齐鲁工业大学获得学士学位,主要研究方向为生物医学图像处理。E-mail:mengqi8850@163.com

    孙正:孙 正(1977—),女,河北保定人,博士,教授,硕士研究生导师,1999年、2004年于天津大学分别获得工学学士和工学博士学位,主要从事生物成像技术和生物医学信号处理等方面的研究。E-mail:sunzheng@ncepu.edu.cn

    通讯作者:

    孙正,E-mail:sunzheng@ncepu.edu.cn

  • 中图分类号: R445;TP391.41

Solutions to inhomogeneous and unstable illumination in biological photoacoustic tomography

Funds: Supported by National Natural Science Foundation of China (No. 62071181)
More Information
  • 摘要: 在生物组织光声层析成像(Photoacoustic Tomography, PAT)算法中,为了简化问题,通常假设在均匀和稳定照明的理想情况下,重建组织的初始声压分布图、光吸收能量分布图和光学特性参数分布图。但在实际应用中,当光在生物组织中传播时,会出现光衰减和光通量分布不均匀的情况,导致重建精度下降。本文对非理想条件下用于补偿由不均匀和不稳定照明所致PAT成像误差的主要方法进行归纳和总结,讨论不同方法的优势和不足。
  • 图  1  采用稀疏分解法的PAT图像重建结果[15]。 (a)仿体的几何结构图;(b)光吸收能量分布图;(c)光通量分布图;(d)光吸收系数分布图

    Figure  1.  Results of PAT image reconstruction by using the sparse decomposition algorithm[15]. (a) Geometry of the phantom to be imaged; (b) optical absorption distribution; (c) light fluence distribution; (d) optical absorption coefficient

    图  2  充分激活RSFP前后的三维光声图像[19]。(a)激活前;(b)激活后

    Figure  2.  Three-dimensional photoacoustic images (a) before and (b) after full activation of RSFPs[19]. Reprinted with permission from © The Optical Society.

    图  3  PA-AO联合成像实验装置原理图[20]

    Figure  3.  Schematic diagram of experimental setup of PA-AO joint imaging[20]. Reprinted with permission from © The Optical Society.

    图  4  采用PA-AO光谱组合法得到的光声图像[20]。(a) λ=755 nm时从side1(左图)和side2(右图)照射介质得到的光声图像;(b) λ=780 nm时从side1(左图)和side2(右图)照射介质得到的光声图像;(c) λ=755 nm(左图)和λ=780 nm(右图)时补偿光通量后的光声图像

    Figure  4.  PA images obtained by using PA-AO spectral combination method[20]. (a) PA images by exciting the medium from side 1 (Left) and side 2 (Right) when λ=755 nm; (b) PA images by exciting the medium from side 1 (Left) and side 2 (Right) when λ=780 nm; (c) PA images of λ=755 nm (Left) and λ=780 nm (Right) after light fluence compensation. Reprinted with permission from © The Optical Society.

    图  5  手持式乳腺PAUS成像装置示意图[23]。(a)成像装置示意图;(b)中央切割平面的光通量

    Figure  5.  Schematic diagram of handheld breast PAUS setup[23]. (a) Imaging setup; (b) map of light fluence in the central cut plane

    图  6  补偿光通量前后的乳腺图像[23]。(a)未补偿光通量的PAT图像;(b)补偿光通量后的PAT图像;(c)未补偿光通量的PAUS图像;(d)补偿光通量的PAUS图像

    Figure  6.  Breast images before and after compensation for light fluence[23]. PAT image before (a) and after (b) light fluence compensation; PAUS dual-modal image before (c) and after (d) light fluence compensation

    图  7  光声-被动超声融合成像原理示意图[24]

    Figure  7.  Schematic diagram of photoacoustic-passive ultrasonic fusion imaging[24]

    图  8  光声与光声-被动超声融合图像对比[24]。(a)光声图像;(b)光声-被动超声融合图像

    Figure  8.  Comparison of (a) photoacoustic images and (b) photoacoustic-passive ultrasonic fusion images[24]

    图  9  PAT-DOT的成像结果[28]。 (a) DOT测量的光吸收系数和散射系数分布图;(b)组织表面的光通量分布图;(c)补偿光通量之前的PAT图像;(d)补偿光通量之后的PAT图像

    Figure  9.  Results of the PAT-DOT method[28]. (a) The distributions of optical absorption coefficient and scattering coefficient measured by DOT; (b) light fluence on the phantom surface; PAT images (c) before and (d) after compensating for light fluence

    图  10  光子在注入点1、标记体积2和检测器位置3之间的轨迹示意图[30]

    Figure  10.  Schematic of photon trajectories between injection point 1, labeling volume 2 and detector position 3[30]

    图  11  采用表面光增强法的PAY图像重建结果[35]

    Figure  11.  Results of PAT image reconstruction with the augmented PAT[35]. Reprinted with permission from © The Optical Society.

    图  12  采用旋转照明的乳房三维PAT系统示意图[36]。(a) PAT系统;(b)乳房假体的二维横截面

    Figure  12.  An illustration of 3D breast PAT system employing the rotating partial illumination design[36]. (a) Imaging system; (b) 2D cross-section of the numerical breast phantom

    图  13  非平稳照明示意图[37]

    Figure  13.  Schematic diagram of non-stationary illumination[37]. Reprinted with permission from © The Optical Society.

    图  14  内置光捕捉器的高频光声成像探头示意图[39]

    Figure  14.  Schematic diagram of high-frequency photoacoustic imaging probe with built-in light catcher[39]

    图  15  采用光捕捉器增强照明(a)前(b)后的光声图像对比[39]

    Figure  15.  Comparison of photoacoustic images before (a) and after (b) enhanced illumination by using light catcher[39]

    图  16  3D打印的样品室、支架、超声换能器阵列和待成像目标的(a)装配图和(b)实物照片[41]

    Figure  16.  (a) Assembly diagram and (b) photograph of 3D-printed sample chamber, entire holder, ultrasound matrix array transducer and imaged target[41]

    图  17  (a)光纤扩散器实物照片;(b)光纤扩散器照明[42]

    Figure  17.  (a) Photograph of the fiber diffuser; (b) fiber diffuse illumination[42]

    图  18  (a)外部照明与(b)内部照明PAT图像对比[42]

    Figure  18.  PAT images with (a) external and (b) internal illumination[42]

    表  1  补偿PAT光通量变化的主要方法对比

    Table  1.   Comparison of main methods of compensating for variations in light fluence in PAT

    方法优点缺点适用范围
    稀疏分解法无需组织光学特性的先验知识,
    不必求解光辐射传输方程,建模
    误差不累积在图像重建结果中
    不适用于光吸收系数缓慢
    变化的目标,非均匀边界
    光照可能引入误差
    光照非均匀性高、量化精度高
    以及稳定性要求高的静态
    目标的成像
    基于成像模型
    的方法
    减少低光通量区域的噪声和伪影,
    减少有限角度测量和声速不均匀
    分布所致重建误差
    噪声抑制效果差,需要较大
    内存,很难应用于高分辨率、
    大规模、实时图像重建
    任意光照条件、平面/圆柱/
    球面测量几何、静态物体的
    小规模成像
    基于荧光蛋白
    的方法
    光学对比度高,分辨率高,可校正
    运动区域的光通量,可在不同
    波长下校正光通量
    可逆蛋白种类有限,波长依赖性不同入射光波长、静态/
    动态目标的成像
    光声-声光
    光谱组合法
    无需组织光学特性的先验知识,
    不依赖于光传输模型的假设
    波长依赖性,忽略局部
    散射变化和超声标记体积
    的影响
    不同入射光波长、静态目标
    的成像
    光声-超声双模态
    成像融合法
    减少由于反向散射和漫反射引起
    的光吸收系数的估算误差
    系统分辨率低,校准函数简单,
    漫反射图像可能发生畸变,校准
    方程不适用于气泡
    分辨率要求低、目标中气泡含量少
    且光吸收系数误差范围大的
    静态目标成像
    下载: 导出CSV

    表  2  精准估计PAT光通量的主要方法对比

    Table  2.   Comparison of main methods for accurately estimating light fluence in PAT

    方法优点不足适用范围
    DOT成像精度高假设Gruneisen系数为常数,增加
    成像系统及其操作的复杂度
    具有相同成分或热力学
    特性差异不明显的目标
    光声-声光
    信号组合
    无需有关组织光学特性的先验知识假设光子的平均自由程大于标记体的线性
    维数,间接测量光子功率会引入误差
    光学特性未知的目标
    表面光增强同步估计光吸收系数、光散射系数和
    Gruneisen系数,估计精度高
    无法确定最小化问题的唯一性热力学特性差异明显的目标
    下载: 导出CSV

    表  3  PAT照明模式的比较

    Table  3.   Comparison of two schemes of illumination in PAT

    照明模式优点不足适用范围
    外部照明旋转照明光穿透性强数据不一致性体积较小的目标
    非平稳照明改善数据的不一致性,成像深度大组织内部光束重叠体积较小的目标
    光捕捉器
    增强照明
    解决表面光反射问题,样品表面光照相对均匀,改善深层组织的成像质量对成像质量的改善有限,很难
    用于表面不平坦的目标
    表面平坦的目标
    优化的三维
    PAT照明
    样品表面光照均匀,成像深度大设备灵活性差,重建精度受限孤立目标的三维PAT
    内部照明光纤扩散器照明成像深度高,系统兼容性强穿透深度受到光纤扩散器与组织
    之间光衰减的限制,难以实现
    特定方向的照明
    大型目标,内部器官的成像
    下载: 导出CSV
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    WANG H, FENG J SH, CHENG ZH X. Image denoising based on local path feature in formation neural network[J]. Chinese Journal of Liquid Crystals and Displays, 2020, 35(1): 70-79. (in Chinese) doi: 10.3788/YJYXS20203501.0070
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出版历程
  • 收稿日期:  2020-08-12
  • 修回日期:  2020-09-21
  • 网络出版日期:  2021-02-03
  • 刊出日期:  2021-04-01

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