Robust anisotropic diffusion to produce enhanced statistical parametric map from noisy fMR1
Robust anisotropic diffusion to produce enhanced statistical parametric map from noisy fMR1
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DOI：
10.1016/j.cviu.2005.04.004
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发表时间：
2005-09-01
影响因子：
4.5
通讯作者：
Cho, ZH
中科院分区：
文献类型：
--
作者：
Kim, HY;Giacomantone, J;Cho, ZH
本文提出了一种新的、简单而优雅的技术，可以从嘈杂的功能磁共振成像 (fMRI) 数据中获取增强的统计参数图 (SPM)。该技术基于稳健的各向异性扩散 (RAD)，这是一种通常用作边缘保留滤波器的技术。将 RAD 直接应用于 fMRI 数据是行不通的，因为在这种情况下，RAD 将对 fMRI 结构信息执行边缘保留过滤，而不是增强其功能信息。 RAD 可以直接应用于 SPM，但在这种情况下，只能实现 SPM 质量的小幅改进，因为未考虑原始 fMRI。为了克服这些困难，我们建议从噪声 fMRI 中估计 SPM，计算 SPM 空间中的扩散系数，然后使用先前计算的系数在结构信息去除的 fMRI 数据中执行扩散。迭代这些步骤直到收敛。我们在模拟和真实的功能磁共振成像图像中测试了这项新技术，产生了令人惊讶的锐利和无噪声的 SPM，并且具有更高的统计显着性。我们还描述了如何自动估计适当的尺度参数。 (c) 2005 Elsevier Inc. 保留所有权利。
This paper presents a new, simple, and elegant technique to obtain enhanced statistical parametric maps (SPMs) from noisy functional magnetic resonance imaging (fMRI) data. This technique is based on the robust anisotropic diffusion (RAD), a technique normally used as an edge-preserving filter. A direct application of the RAD to the fMRI data does not work, because in this case RAD would perform an edge-preserving filtering of the fMRI structural information, instead of enhancing its functional information. The RAD can be applied directly to SPM but, in this case, only a small improvement of the SPM quality can be achieved, because the originating fMRI is not taken into account. To overcome these difficulties, we propose to estimate the SPM from the noisy fMRI, compute the diffusion coefficients in the SPM space, and then perform the diffusion in the structural information-removed fMRI data using the coefficients previously computed. These steps are iterated until convergence. We have tested the new technique in both simulated and real fMRI images, yielding surprisingly sharp and noiseless SPMs with increased statistical significance. We also describe how to automatically estimate an appropriate scale parameter. (c) 2005 Elsevier Inc. All rights reserved.