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重新探讨扩散方向变换。

Diffusion orientation transform revisited.

机构信息

Benito Menni Complex Assistencial en Salut Mental, Barcelona, Spain.

出版信息

Neuroimage. 2010 Jan 15;49(2):1326-39. doi: 10.1016/j.neuroimage.2009.09.067. Epub 2009 Oct 6.

Abstract

Diffusion orientation transform (DOT) is a powerful imaging technique that allows the reconstruction of the microgeometry of fibrous tissues based on diffusion MRI data. The three main error sources involving this methodology are the finite sampling of the q-space, the practical truncation of the series of spherical harmonics and the use of a mono-exponential model for the attenuation of the measured signal. In this work, a detailed mathematical description that provides an extension to the DOT methodology is presented. In particular, the limitations implied by the use of measurements with a finite support in q-space are investigated and clarified as well as the impact of the harmonic series truncation. Near- and far-field analytical patterns for the diffusion propagator are examined. The near-field pattern makes available the direct computation of the probability of return to the origin. The far-field pattern allows probing the limitations of the mono-exponential model, which suggests the existence of a limit of validity for DOT. In the regimen from moderate to large displacement lengths the isosurfaces of the diffusion propagator reveal aberrations in form of artifactual peaks. Finally, the major contribution of this work is the derivation of analytical equations that facilitate the accurate reconstruction of some orientational distribution functions (ODFs) and skewness ODFs that are relatively immune to these artifacts. The new formalism was tested using synthetic and real data from a phantom of intersecting capillaries. The results support the hypothesis that the revisited DOT methodology could enhance the estimation of the microgeometry of fiber tissues.

摘要

扩散方向变换(DOT)是一种强大的成像技术,它允许根据扩散 MRI 数据重建纤维组织的微观结构。涉及这种方法的三个主要误差源是 q 空间的有限采样、球谐级数的实际截断以及使用单指数模型来衰减测量信号。在这项工作中,提出了一种详细的数学描述,为 DOT 方法提供了扩展。特别是,研究并澄清了在 q 空间中使用有限支持的测量所涉及的限制,以及谐波级数截断的影响。还研究了扩散传播子的近场和远场分析模式。近场模式可直接计算返回原点的概率。远场模式允许探测单指数模型的局限性,这表明 DOT 存在有效性限制。在从中等到大位移长度的范围内,扩散传播子的等位面显示出形式上的异常,表现为人为的峰值。最后,这项工作的主要贡献是推导出了分析方程,这些方程有助于准确重建一些相对不受这些伪影影响的各向异性分布函数(ODF)和偏态 ODF。新的形式主义使用来自交叉毛细血管的幻影的合成和真实数据进行了测试。结果支持了这样一种假设,即经过重新审视的 DOT 方法可以提高纤维组织微观结构的估计。

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