Division of Computational Sciences in Mathematics, National Institute for Mathematical Sciences, Korea.
Phys Med Biol. 2012 Jun 7;57(11):3643-59. doi: 10.1088/0031-9155/57/11/3643.
Magnetic resonance electrical impedance tomography (MREIT) is a non-invasive method to visualize cross-sectional electrical conductivity and/or current density by measuring a magnetic flux density signal when an electrical current is injected into a subject. In the MREIT system, it is crucial to reduce the scan duration while maintaining spatial resolution and contrast for practical in vivo implementation. The purpose of the study is to optimize the measured magnetic flux density using an interleaved multiple-echo pulse sequence (injected current nonlinear encoding) that acquires each spatial position multiple times, although these pixels vary between echoes in their signal-to-noise ratio due to (a) T2 decay and (b) the current density passing through the pixel. Using the acquired multiple measured magnetic flux densities, the noise level for the measured magnetic flux density B(z) at each pixel is estimated using the relationship between the intensity of the magnitude and the width of the injected current. We determine an optimal combination of the multiply acquired magnetic flux densities, which optimally reduces the random noise artifacts. We develop a new denoising technique and apply it to a recovered conductivity distribution with a known noise level of the recovered magnetic flux density, which is designed to provide a stable internal conductivity distribution, while sustaining resolution. The proposed method uses three key steps: the first step is optimizing the magnetic flux density by using the multiple-echo magnetic flux densities at each pixel, the second step is estimating the noise level of this optimized magnetic flux density and the third step is applying a denoising technique using the pixel-specific estimated noise level. Numerical simulation experiments using a three-dimensional cylindrical phantom model validated the proposed method. Multiple-echo B(z) data were generated, including in short T2 or low spin-density regions, as a function of T*2 and the temporal extent of the injected current. In the simulation experiment, comparing between an equally averaged and the optimized B(z) methods, relative L2-mode errors were 0.053 and 0.024, respectively. In an actual imaging experiment of an agarose gel filled with objects of various conductivities and shapes, we acquired six echoes per repetition time. The optimal weighting factors minimized the effects of noise in B(z), and provided reconstructed conductivity maps that suppressed noise artifacts that normally accumulate in the low signal-to-noise-ratio defect regions.
磁共振电阻抗断层成像（MREIT）是一种通过向受试者注入电流来测量磁通密度信号来可视化横截面电导率和/或电流密度的非侵入性方法。在 MREIT 系统中，至关重要的是在保持空间分辨率和对比度的同时减少扫描持续时间，以便在实际的体内实现。本研究的目的是通过使用交错的多回波脉冲序列（注入电流非线性编码）来优化测量的磁通密度，该序列多次获取每个空间位置，尽管由于（a）T2 衰减和（b）通过像素的电流密度，这些像素在回波之间在信噪比上有所不同。使用获得的多个测量的磁通密度，使用幅度的强度与注入电流的宽度之间的关系来估计每个像素处测量的磁通密度 B(z)的噪声水平。我们确定了多次获取的磁通密度的最佳组合，该组合可最佳地减少随机噪声伪影。我们开发了一种新的去噪技术，并将其应用于具有已知恢复磁通密度噪声水平的恢复电导率分布，该技术旨在提供稳定的内部电导率分布，同时保持分辨率。该方法使用三个关键步骤：第一步是使用每个像素的多回波磁通密度来优化磁通密度，第二步是估计此优化磁通密度的噪声水平，第三步是使用像素特定的估计噪声水平应用去噪技术。使用三维圆柱模型的数值模拟实验验证了所提出的方法。生成了多回波 B(z)数据，包括短 T2 或低自旋密度区域，作为 T*2 和注入电流的时间范围的函数。在模拟实验中，将等均值和优化的 B(z)方法进行比较，相对 L2 模式误差分别为 0.053 和 0.024。在充满各种电导率和形状的物体的琼脂糖凝胶的实际成像实验中，我们在每个重复时间内采集了六个回波。最优加权因子最小化了 B(z)中的噪声影响，并提供了重建电导率图，抑制了通常在低信噪比缺陷区域中累积的噪声伪影。
