Efficient and robust computation of PDF features from diffusion MR signal
Efficient and robust computation of PDF features from diffusion MR signal
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DOI：
10.1016/j.media.2009.06.004
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发表时间：
2009-10-01
影响因子：
10.9
通讯作者：
Brun, Luc
中科院分区：
文献类型：
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作者：
Assemlal, Haz-Edine;Tschumperle, David;Brun, Luc
我们提出了一种利用扩散磁共振成像来估计组织微结构的各种特征的方法。所考虑的特征是从位移概率密度函数(PDF)设计的。该估计基于两个步骤：首先通过由高斯-拉盖尔函数和球谐函数组成的级数展开来逼近信号；然后在有限维空间上进行投影。此外，我们建议解决对莱斯噪声的稳健性破坏活体获取的问题。我们的特征估计被表示为一个变分最小化过程，该过程导致了一个对噪声具有鲁棒性的变分框架。这种方法在样本数量方面非常灵活，并且能够计算局部组织结构的大集合的各种特征。我们用在临床时间范围内采集的合成体模和真实磁共振数据集上的结果证明了该方法的有效性。(C)2009爱思唯尔B.V.保留所有权利。
We present a method for the estimation of various features of the tissue micro-architecture using the diffusion magnetic resonance imaging. The considered features are designed from the displacement probability density function (PDF). The estimation is based on two steps: first the approximation of the signal by a series expansion made of Gaussian-Laguerre and Spherical Harmonics functions; followed by a projection on a finite dimensional space. Besides, we propose to tackle the problem of the robustness to Rician noise corrupting in-vivo acquisitions. Our feature estimation is expressed as a variational minimization process leading to a variational framework which is robust to noise. This approach is very flexible regarding the number of samples and enables the computation of a large set of various features of the local tissues structure. We demonstrate the effectiveness of the method with results on both synthetic phantom and real MR datasets acquired in a clinical time-frame. (C) 2009 Elsevier B.V. All rights reserved.