一种改进的基于一步NOSER的MIT重建方法

Qiang Du, B. Bai, Peipei Pang, Li Ke
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引用次数: 6

摘要

磁感应层析成像(MIT)是一种新型的生物层析技术,具有无害、无创、方便等特点。图像重建算法的分辨率和速度是提高MIT系统性能和应用的关键。牛顿-一步误差重构(newton - 1 - step Error reconstruction, NOSER)是MIT中常用的一种重构算法,但在此过程中,由于Hessian矩阵的不适定,原始数据的微小变化会对重构图像产生影响。本文将特征值阈值(ET)用于Hessian矩阵的修正,对该方法进行了改进。与NOSER和Tikhonov正则化相比,该算法可以提高图像的分辨率和抗噪声特性。由于该算法没有迭代过程,因此可以提高成像速度。不同成像模型的重建结果表明,该算法有可能提高MIT系统的性能,促进该技术的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Reconstruction Method of MIT Based on One-Step NOSER
Magnetic induction tomography (MIT) is a new biologic tomography technology with the feature of harmless, non-invasive and convenience. The resolution and speed of image reconstruction algorithm is critical for improving the performance of MIT system and its application. Newton-One-Step Error Reconstruct or (NOSER) is a common reconstruction algorithm in MIT, but the slight variations of original data will impact the reconstructed images because of Hessian matrix which is ill-posed in the process of NOSER. In this paper, the NOSER was improved by eigen value threshold(ET) which was used to modify Hessian matrix. Compared with NOSER and Tikhonov regularization, the algorithm might improve the image resolution and anti-noise characteristic. Because the algorithm has no iterative procedure, it also was able to enhance imaging speed. The reconstruction results of varied imaging models demonstrate that the algorithm could potentially improve the performance of the MIT system and promote the application of the technology.
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