基于参数水平集的电容层析成像图像重建

Rui Li, Yongfu Zhang, Lihui Peng, X. Liao
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引用次数: 1

摘要

图像重建算法是电容层析成像(ECT)的关键,目前尚处于研究的热点阶段。随着图像重建算法的发展,高质量图像一直是电痉挛治疗面临的关键挑战。本文提出了一种利用参数水平集方法实现高质量电痉挛图像重建的新算法。基于敏感区介电常数分布与电容值的关系,参数水平集算法能够实现绝对值ECT重构。本文给出了用参数水平集法(PLS)重建不同漏水点介电常数剖面的模拟结果。与LBP正则化、landweber迭代算法和全变分正则化等现有图像重建算法相比,该方法具有更好的图像质量,特别是在高对比度多相数据下。PLS采用高斯径向基函数(GRBF),大大减少了未知量。参数水平集方法避免了计算过程中正则化系数的问题,减少了图像重建中的不适定问题。该方法具有较好的图像质量和较好的信噪比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Image Reconstruction For Electrical Capacitance Tomography Using Parametric Level Set
Image reconstruction algorithm is essential for electrical capacitance tomography (ECT), which is still in the stage of popular research. With the development of image reconstruction algorithm, high-quality image is the key challenge for ECT all long. The paper proposes a kind of novel-image-reconstruction-algorithm for ECT using parametric level-set method to obtain high-image quality. Based on the relationship between dielectric constant distribution and capacitance value in the sensitivity area, parametric level set algorithm is capable of realizing absolute values ECT reconstruction. The paper presented simulation results of reconstructing the permittivity profiles of different water leakage using parametric level set method (PLS). Comparing with the state of the art image reconstruction algorithm, such as LBP regularization, landweber iterative algorithm and total variational regularization, the proposed method has better image quality, especially with high contrast multiphase data. PLS adopts Gaussian radial basis function (GRBF), which considerably reduces the number of unknowns. The parametric level set method can avoid the problem of regularization coefficients involved in the calculation process and reduce the Ill-posed Problem of image reconstruction. The proposed PLS method has demonstrated the superior image quality and better noise ratio (SNR).
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