Gao Nuo, He Bin
Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
IEEE Trans Biomed Eng. 2008 May;55(5):1530-8. doi: 10.1109/TBME.2008.918565.
We have developed a novel magnetic resonance electrical impedance tomography (MREIT) algorithm-current reconstruction MREIT algorithm-for noninvasive imaging of electrical impedance distribution of a biological system using only one component of magnetic flux density. The newly proposed algorithm uses the inverse of Biot-Savart Law to reconstruct the current density distribution, and then, uses a modified J-substitution algorithm to reconstruct the conductivity image. A series of computer simulations has been conducted to evaluate the performance of the proposed current reconstruction MREIT algorithm with simulation settings for breast cancer imaging applications, with consideration of measurement noise, current injection strength, size of simulated tumors, spatial resolution, and position dependency. The present simulation results are highly promising, demonstrating the high spatial resolution, high accuracy in conductivity reconstruction, and robustness against noise of the proposed algorithm for imaging electrical impedance of a biological system. The present MREIT method may have potential applications to breast cancer imaging and imaging of other organs.
我们开发了一种新型磁共振电阻抗断层成像(MREIT)算法——电流重建MREIT算法,用于仅使用磁通密度的一个分量对生物系统的电阻抗分布进行无创成像。新提出的算法利用毕奥-萨伐尔定律的逆运算来重建电流密度分布,然后,使用改进的J-替代算法来重建电导率图像。已经进行了一系列计算机模拟,以评估所提出的电流重建MREIT算法在乳腺癌成像应用模拟设置下的性能,同时考虑了测量噪声、电流注入强度、模拟肿瘤大小、空间分辨率和位置依赖性。目前的模拟结果非常有前景,证明了所提出的用于生物系统电阻抗成像算法具有高空间分辨率、电导率重建的高精度以及对噪声的鲁棒性。目前的MREIT方法可能在乳腺癌成像和其他器官成像方面有潜在应用。