基于全变分法重建光声图像

张砚; 汪源源; 李伟; 张建秋; 李旦; 胡波

doi:10.3788/OPE.20122001.0204

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基于全变分法重建光声图像

信息科学 | 更新时间：2020-08-12

- 基于全变分法重建光声图像
- Reconstruction of photoacoustic image based on total variation
- 光学精密工程 2012年20卷第1期页码：204-212
- 作者机构：
  
  复旦大学电子工程系上海,200433
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.10974035)();上海市优秀学科带头人计划资助项目(No.10XD1400600)()
- DOI：10.3788/OPE.20122001.0204
  中图分类号： Q-334;R318.51
- 收稿日期：2011-08-05，
  
  修回日期：2011-10-10，
  
  网络出版日期：2012-01-25，
  
  纸质出版日期：2012-01-25
- 稿件说明：
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张砚, 汪源源, 李伟, 张建秋, 李旦, 胡波. 基于全变分法重建光声图像[J]. 光学精密工程, 2012,20(1): 204-212

ZHANG Yan, WANG Yuan-yuan, LI Wei, ZHANG Jian-qiu, LI Dan, HU Bo. Reconstruction of photoacoustic image based on total variation[J]. Editorial Office of Optics and Precision Engineering, 2012,20(1): 204-212
张砚, 汪源源, 李伟, 张建秋, 李旦, 胡波. 基于全变分法重建光声图像[J]. 光学精密工程, 2012,20(1): 204-212 DOI： 10.3788/OPE.20122001.0204.

ZHANG Yan, WANG Yuan-yuan, LI Wei, ZHANG Jian-qiu, LI Dan, HU Bo. Reconstruction of photoacoustic image based on total variation[J]. Editorial Office of Optics and Precision Engineering, 2012,20(1): 204-212 DOI： 10.3788/OPE.20122001.0204.

摘要

针对光声成像在实际应用中涉及的采样数据不足

提出了一种基于全变分法的光声图像重建方法。通过计算重建图像的模拟信号与实际信号的残差来更新图像

进行迭代以获取重建图像。在迭代重建的过程中引入压缩传感理论中的全变分法

通过梯度下降法得到全变分最小的图像。通过数值仿真

模拟了在不足采样情况下的图像重建。结果表明

全变分重建法的重建效果比滤波反投影法、反卷积重建算法及代数重建算法等3种方法更好。在30个采样点的情况下

重建图像的峰值信噪比值比上述3种算法的重建结果分别高出30.98

22.09和8.35 dB。另外

仿体实验结果也表明该方法能更有效地避免噪声的干扰。

Abstract

For insufficient sampling data existing in the practical application of Photoacoustic Tomography (PAT)

a reconstruction method based on total variation method was proposed for photoacoustic imaging to solve this problem. The residual between the real signals and the simulated ones from the reconstructed image was calculated for the update image

and the iteration was implemented to obtain the reconstruction image. During the process of iteration

the total variation method in the compressed sensing was utilized to obtain the image with the smallest total variation value by the gradient descent method. Through the numerical simulation

the image reconstruction in the case of insufficient sampling data was accomplished. The results demonstrate that the reconstruction method based on the total variation has better performance as compared with the filtered back-projection method

deconvolution reconstruction method and algebraic reconstruction method. For the 30 sampling points

the peak signal-noise ratio of the reconstructed image is 30.98

22.09

8.35 dB higher than those reconstructed by tree kinds of other methods metioned above

respectively. The result of in vitro experiment also shows that this method is more effective for noise suppression.

关键词

Keywords

references

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