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使用低振幅电流的磁共振电阻抗成像中的对比度和空间分辨率。

Contrast and spatial resolution in MREIT using low amplitude current.

作者信息

Birgul Ozlem, Hamamura Mark J, Muftuler L Tugan, Nalcioglu Orhan

机构信息

Tu and Yuen Center for Functional Onco Imaging, University of California Irvine, USA.

出版信息

Phys Med Biol. 2006 Oct 7;51(19):5035-49. doi: 10.1088/0031-9155/51/19/020. Epub 2006 Sep 19.

Abstract

Magnetic resonance-electrical impedance tomography employs low amplitude currents injected or induced inside an object. The additional magnetic field due to these currents results in a phase in the MR images. In this study, a modified fast spin-echo sequence was used to measure this magnetic field, which is obtained by scaling the MR phase image. A finite element method with first order triangular elements was used for the solution of the forward problem. An iterated sensitivity matrix-based algorithm was developed for the inverse problem. The resulting ill-conditioned matrix equation was regularized using the Tikhonov method and solved using a conjugate gradient solver. The spatial and contrast resolution of the technique was tested using agarose gel phantoms. A circular phantom with 7 cm diameter and 1 cm thickness is used in the phantom experiments. The amplitude of the injected current was 1 mA. 3, 5 and 8 mm diameter insulators and high conductor objects are used for the spatial resolution study and an average full-width half-maximum value of 4.7 mm is achieved for the 3 mm insulator case. For the contrast analysis, the conductivity of a 15 mm object is varied between 44% and 500% with respect to the background and results are compared to the ideal reconstruction.

摘要

磁共振电阻抗断层成像技术利用注入或感应到物体内部的低振幅电流。这些电流产生的附加磁场会在磁共振图像中导致相位变化。在本研究中,采用了一种改进的快速自旋回波序列来测量该磁场,该磁场通过对磁共振相位图像进行缩放获得。使用一阶三角形单元的有限元方法来求解正问题。针对逆问题开发了一种基于迭代灵敏度矩阵的算法。使用蒂霍诺夫方法对所得的病态矩阵方程进行正则化,并使用共轭梯度求解器进行求解。使用琼脂糖凝胶体模对该技术的空间分辨率和对比度分辨率进行了测试。在体模实验中使用了直径7厘米、厚度1厘米的圆形体模。注入电流的幅度为1毫安。使用直径为3毫米、5毫米和8毫米的绝缘体和高导体物体进行空间分辨率研究,对于3毫米绝缘体的情况,平均半高宽值达到4.7毫米。对于对比度分析,将一个15毫米物体的电导率相对于背景在44%至500%之间变化,并将结果与理想重建结果进行比较。

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