脑电阻抗断层成像中电导率分布的联合重建方法

IF 1.2 4区 数学 Q2 MATHEMATICS, APPLIED
Yanyan Shi, Yajun Lou, Meng Wang, Shuo Zheng, Zhiwei Tian, Feng Fu
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引用次数: 1

摘要

电阻抗断层成像(EIT)是一种很有前途的医学成像技术。使用这种技术,可以可视化病理相关的电导率变化。然而,电导率分布的重建是一个严重的不适定逆问题,这对EIT技术提出了很大的挑战。特别是在脑电成像中,不规则的、多层的头部结构以及低电导率的颅骨给准确重建带来了更多的困难。针对这一问题,提出了一种将Tikhonov正则化与去噪算法相结合的脑电导率重构方法。利用该方法对三层头部模型不同脑叶的脑出血图像进行了重建。同时重建脑出血和继发性缺血。同时,研究了噪声对系统的影响,评价了系统的抗噪声性能。此外,还进行了头部形状变形下的图像重建。通过计算模糊半径和结构相似度对所提出的重建方法进行了定量估计。仿真实验进一步验证了所提方法的有效性。定性和定量结果均表明,该方法在成像电导率分布方面优于Tikhonov正则化方法。这项工作将为基于EIT的医学成像提供精确重建的替代方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Imaging of conductivity distribution based on a combined reconstruction method in brain electrical impedance tomography
Electrical impedance tomography (EIT) is a promising technique in medical imaging. With this technique, pathology-related conductivity variation can be visualized. Nevertheless, reconstruction of conductivity distribution is a severely ill-posed inverse problem which poses a great challenge for the EIT technique. Especially in brain EIT, irregular and multi-layered head structure along with low-conductivity skull brings more difficulties for accurate reconstruction. To address such problems, a novel reconstruction method which combines Tikhonov regularization with denoising algorithm is proposed for imaging conductivity distribution in brain EIT. With the proposed method, image reconstruction of intracerebral hemorrhage in different brain lobes of a three-layer head model is conducted. Besides, simultaneous reconstruction of intracerebral hemorrhage and secondary ischemia is performed. Meanwhile, the impact of noise is investigated to evaluate the anti-noise performance. In addition, image reconstructions under head shape deformation are performed. The proposed reconstruction method is also quantitatively estimated by calculating blur radius and structural similarity. Phantom experiments are carried out to further verify the effectiveness of the proposed method. Both qualitative and quantitative results have demonstrated that the proposed combined method is superior to Tikhonov regularization in imaging conductivity distribution. This work would provide an alternative for accurate reconstruction in EIT based medical imaging.
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来源期刊
Inverse Problems and Imaging
Inverse Problems and Imaging 数学-物理:数学物理
CiteScore
2.50
自引率
0.00%
发文量
55
审稿时长
>12 weeks
期刊介绍: Inverse Problems and Imaging publishes research articles of the highest quality that employ innovative mathematical and modeling techniques to study inverse and imaging problems arising in engineering and other sciences. Every published paper has a strong mathematical orientation employing methods from such areas as control theory, discrete mathematics, differential geometry, harmonic analysis, functional analysis, integral geometry, mathematical physics, numerical analysis, optimization, partial differential equations, and stochastic and statistical methods. The field of applications includes medical and other imaging, nondestructive testing, geophysical prospection and remote sensing as well as image analysis and image processing. This journal is committed to recording important new results in its field and will maintain the highest standards of innovation and quality. To be published in this journal, a paper must be correct, novel, nontrivial and of interest to a substantial number of researchers and readers.
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