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纤维球成像

Fiber ball imaging.

作者信息

Jensen Jens H, Russell Glenn G, Helpern Joseph A

机构信息

Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.

Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Neurosciences Sciences, Medical University of South Carolina, Charleston, SC, USA.

出版信息

Neuroimage. 2016 Jan 1;124(Pt A):824-833. doi: 10.1016/j.neuroimage.2015.09.049. Epub 2015 Oct 1.

Abstract

By modeling axons as thin cylinders, it is shown that the inverse Funk transform of the diffusion MRI (dMRI) signal intensity obtained on a spherical shell in q-space gives an estimate for a fiber orientation density function (fODF), where the accuracy improves with increasing b-value provided the signal-to-noise ratio is sufficient. The method is similar to q-ball imaging, except that the Funk transform of q-ball imaging is replaced by its inverse. We call this new approach fiber ball imaging. The fiber ball method is demonstrated for healthy human brain, and fODF estimates are compared to diffusion orientation distribution function (dODF) approximations obtained with q-ball imaging. The fODFs are seen to have sharper features than the dODFs, reflecting an enhancement of the higher degree angular frequencies. The inverse Funk transform of the dMRI signal intensity data provides a simple and direct method of estimating a fODF. In addition, fiber ball imaging leads to an estimate for the ratio of the fraction of MRI visible water confined to the intra-axonal space divided by the square root of the intra-axonal diffusivity. This technique may be useful for white matter fiber tractography, as well as other types of microstructural modeling of brain tissue.

摘要

通过将轴突建模为细圆柱体,研究表明,在q空间中的球壳上获得的扩散磁共振成像(dMRI)信号强度的逆Funk变换给出了纤维方向密度函数(fODF)的估计值,前提是信噪比足够,随着b值的增加,估计精度会提高。该方法与q球成像类似,只是q球成像的Funk变换被其逆变换所取代。我们将这种新方法称为纤维球成像。本文展示了纤维球方法在健康人脑上的应用,并将fODF估计值与通过q球成像获得的扩散方向分布函数(dODF)近似值进行了比较。可以看到,fODF比dODF具有更清晰的特征,这反映了更高阶角频率的增强。dMRI信号强度数据的逆Funk变换提供了一种简单直接的估计fODF的方法。此外,纤维球成像还能估计出局限于轴突内空间的MRI可见水的分数与轴突内扩散率平方根的比值。这项技术可能对白质纤维束成像以及脑组织的其他类型微观结构建模有用。

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