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电容层析成像中基于卡尔德隆方法的直接图像重建截断半径自适应选择

Adaptive Selection of Truncation Radius in Calderon's Method for Direct Image Reconstruction in Electrical Capacitance Tomography.

作者信息

Sun Shijie, Xu Lijun, Cao Zhang, Sun Jiangtao, Tian Wenbin

机构信息

School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.

Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100191, China.

出版信息

Sensors (Basel). 2019 Apr 29;19(9):2014. doi: 10.3390/s19092014.

DOI:10.3390/s19092014
PMID:31035706
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6539439/
Abstract

Calderon's method has been successfully used for the direct image reconstruction in electrical capacitance tomography. In the method, the truncation radius adopted in numerical integral greatly influences the reconstruction results. In the past, the truncation radius is selected as a constant empirically according to the permittivity distribution pattern and noise level. In this paper, the influence of the truncation radius in Calderon's method on the reconstruction results was first analyzed by numerical simulation. Then, a strategy for adaptive selection of the truncation radius was proposed. The amplitude information of the elements in the scattering transform matrix computed from the Dirichlet-to-Neumann (DN) map was used to determine the range for the truncation radius selection, and the phase information was further used to select a proper truncation radius value within this selection range. Finally, experiments were carried out to verify the strategy. Experimental results showed that small relative image error and good visual effect could be obtained by using the truncation radius selected by the proposed strategy.

摘要

卡尔德隆方法已成功应用于电容层析成像中的直接图像重建。在该方法中,数值积分所采用的截断半径对重建结果有很大影响。过去,截断半径是根据介电常数分布模式和噪声水平凭经验选择为一个常数。本文首先通过数值模拟分析了卡尔德隆方法中截断半径对重建结果的影响。然后,提出了一种截断半径自适应选择策略。利用从狄利克雷 - 诺伊曼(DN)映射计算得到的散射变换矩阵中元素的幅度信息来确定截断半径选择范围,并且进一步利用相位信息在该选择范围内选择合适的截断半径值。最后,进行实验以验证该策略。实验结果表明,采用所提出策略选择的截断半径能够获得较小的相对图像误差和良好的视觉效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe2c/6539439/f8026f9c0309/sensors-19-02014-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe2c/6539439/f8026f9c0309/sensors-19-02014-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe2c/6539439/e3814290cef2/sensors-19-02014-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe2c/6539439/9bb857fec3c2/sensors-19-02014-g010.jpg
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