Suppr超能文献

基于电阻抗断层成像的分段连续平面分层生物组织的稳定重建。

Stable reconstruction of piecewise continuous plane stratified biological tissues via electrical impedance tomography.

机构信息

Engineering School, Kinneret College on the Sea of Galilee, Israel.

出版信息

IEEE Trans Biomed Eng. 2010 May;57(5):1227-33. doi: 10.1109/TBME.2009.2038168. Epub 2010 Feb 5.

Abstract

Image reconstruction in electrical impedance tomography is, generally, an ill-posed nonlinear inverse problem. Regularization methods are widely used to ensure a stable solution. Herein, we present a case study, which uses a novel electrical impedance tomography method for reconstruction of layered biological tissues with piecewise continuous plane-stratified profiles. The algorithm implements the recently proposed reconstruction scheme for piecewise constant conductivity profiles, utilizing Legendre expansion in conjunction with improved Prony method. It is shown that the proposed algorithm is capable of successfully reconstructing piecewise continuous conductivity profiles with moderate slop. This reconstruction procedure, which calculates both the locations and the conductivities, repetitively provides inhomogeneous depth discretization, i.e., the depths grid is not equispaced. Incorporation of this specific inhomogeneous grid in the widely used mean least square reconstruction procedure results in a stable and accurate reconstruction, whereas, the commonly selected equispaced depth grid leads to unstable reconstruction. This observation establishes the main result of our investigation, highlighting the impact of physical phenomenon (the image series expansion) on electrical impedance tomography, leading to a physically motivated stabilization of the inverse problem, i.e., an inhomogeneous depth discretization renders an inherent regularization of the mean least square algorithm. The effectiveness and the significance of inhomogeneous discretization in electrical impedance tomography reconstruction procedure is further demonstrated and verified via numerical simulations.

摘要

电阻抗断层成像中的图像重建通常是一个不适定的非线性反问题。正则化方法被广泛用于确保稳定的解。本文提出了一种新的电阻抗断层成像方法,用于重建具有分段连续平面分层轮廓的分层生物组织。该算法实现了最近提出的用于分段常导率轮廓的重建方案,利用勒让德展开结合改进的普朗尼方法。结果表明,所提出的算法能够成功重建具有中等斜率的分段连续电导率轮廓。该重建过程可以同时计算位置和电导率,重复提供非均匀深度离散化,即深度网格不是等距的。在广泛使用的平均最小二乘重建过程中,将这种特殊的非均匀网格纳入其中会导致稳定而准确的重建,而通常选择的等距深度网格会导致不稳定的重建。这一观察结果确立了我们研究的主要结果,强调了物理现象(图像级数展开)对电阻抗断层成像的影响,导致逆问题的物理驱动稳定化,即非均匀深度离散化使得平均最小二乘算法固有正则化。通过数值模拟进一步证明和验证了电阻抗断层成像重建过程中不均匀离散化的有效性和重要性。

相似文献

1
Stable reconstruction of piecewise continuous plane stratified biological tissues via electrical impedance tomography.
IEEE Trans Biomed Eng. 2010 May;57(5):1227-33. doi: 10.1109/TBME.2009.2038168. Epub 2010 Feb 5.
2
Reconstruction of layered biological tissues via electrical impedance tomography.
IEEE Trans Biomed Eng. 2006 Dec;53(12 Pt 1):2464-71. doi: 10.1109/TBME.2006.884638.
4
Solution of the inverse problem of magnetic induction tomography (MIT).
Physiol Meas. 2005 Apr;26(2):S241-50. doi: 10.1088/0967-3334/26/2/023. Epub 2005 Mar 29.
5
A novel approach for EIT regularization via spatial and spectral principal component analysis.
Physiol Meas. 2007 Sep;28(9):1001-16. doi: 10.1088/0967-3334/28/9/003. Epub 2007 Aug 21.
6
Dynamic electrical impedance imaging with the interacting multiple model scheme.
Physiol Meas. 2005 Apr;26(2):S217-33. doi: 10.1088/0967-3334/26/2/021. Epub 2005 Mar 29.
7
Using the GRID to improve the computation speed of electrical impedance tomography (EIT) reconstruction algorithms.
Physiol Meas. 2005 Apr;26(2):S209-15. doi: 10.1088/0967-3334/26/2/020. Epub 2005 Mar 29.
8
Induced current magnetic resonance-electrical impedance tomography.
Physiol Meas. 2005 Apr;26(2):S289-305. doi: 10.1088/0967-3334/26/2/027. Epub 2005 Mar 29.
9
Image reconstruction incorporated with the skull inhomogeneity for electrical impedance tomography.
Comput Med Imaging Graph. 2008 Jul;32(5):409-15. doi: 10.1016/j.compmedimag.2008.04.002. Epub 2008 May 23.
10
Improving the forward solver for the complete electrode model in EIT using algebraic multigrid.
IEEE Trans Med Imaging. 2005 May;24(5):577-83. doi: 10.1109/TMI.2005.843741.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验