计算机应用 ›› 2019, Vol. 39 ›› Issue (10): 3093-3099.DOI: 10.11772/j.issn.1001-9081.2019010076

• 应用前沿、交叉与综合 • 上一篇    下一篇

基于改进固定点迭代方法的深层活体量化光声成像

柳芳艳, 孟静, 司广涛   

  1. 曲阜师范大学 信息科学与工程学院, 山东 日照 276826
  • 收稿日期:2019-01-11 修回日期:2019-03-09 出版日期:2019-10-10 发布日期:2019-04-15
  • 通讯作者: 司广涛
  • 作者简介:柳芳艳(1993-),女,山东济南人,硕士研究生,主要研究方向:医学图像重建与处理;孟静(1977-),女,山东德州人,副教授,博士,主要研究方向:生物医学光声成像;司广涛(1977-),男,山东济宁人,讲师,硕士,主要研究方向:信息处理、计算机网络。
  • 基金资助:
    国家自然科学基金资助项目(61308116)。

Deep in vivo quantitative photoacoustic imaging based on improved fixed point iterative method

LIU Fangyan, MENG Jing, SI Guangtao   

  1. School of Information Science and Engineering, Qufu Normal University, Rizhao Shandong 276826, China
  • Received:2019-01-11 Revised:2019-03-09 Online:2019-10-10 Published:2019-04-15
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61308116).

摘要: 针对限制视图下光声图像的重建伪影问题,提出一种改进的固定点迭代量化光声成像方法。首先,通过传统的反投影重建算法重建由探测器探测到的原始光声压数据,得到原始的光声压图像;接着,利用自适应维纳滤波算法对原始的光声压图像进行滤波去除重建图像伪影;然后,通过光传输模型求解目标成像区域的光通量;最后,进行迭代计算,获得目标组织的光学吸收系数。此外,在求解光通量过程中引入Toast++软件来实现光传输模型的前向求解,提高量化成像的效率和精确性。仿体和活体实验结果表明,与传统固定点迭代方法相比,所提方法能够获取更高质量的光声图像,重建得到的深层量化光声图像中存在较少伪影;量化重建的深层目标组织的光学吸收系数与浅层目标组织的光学吸收系数的数值非常接近,前者约为后者的70%,能实现深层生物组织光学吸收系数的定量重建。

关键词: 量化光声成像, 光学吸收系数, 深层组织, 维纳滤波, Toast++, 光子传输模型

Abstract: Focusing on the reconstruction artifact of photoacoustic images in restricted view, an improved fixed-point iterative quantitative photoacoustic imaging method was proposed. Firstly, the original photoacoustic pressure data detected by the detector were reconstructed by the traditional back projection reconstruction algorithm to obtain the original photoacoustic pressure image. Secondly, the original photoacoustic pressure image was filtered to remove the reconstruction artifact by adaptive Wiener filtering algorithm. Thirdly, the optical transmission model was used to solve the optical flux of the target imaging region. And finally, iterative calculation was performed to obtain the optical absorption coefficient of the target tissue. In addition, Toast++ software was introduced in the process of solving the optical flux to realize the forward solution of the optical transmission model, which improved the efficiency and accuracy of quantitative imaging. The phantom and in vivo experiments show that compared with the traditional fixed-point iterative method, the proposed method can obtain photoacoustic images with higher quality and there are fewer artifacts in the deep quantitative photoacoustic images reconstructed by the method. The optical absorption coefficient of the quantitatively reconstructed deep target tissue is very close to the optical absorption coefficient of the shallow target tissue, the former is about 70% of the latter. As a result, the quantitative reconstruction of the optical absorption coefficient of the deep biological tissue can be implemented by the proposed method.

Key words: quantitative photoacoustic imaging, optical absorption coefficient, deep tissue, Wiener filtering, Toast++, photon transmission model

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