.png){kind=icon}
返回
Characterizing non-Gaussian diffusion by using generalized diffusion tensors
.png){kind=icon}
OA
AI
DOI：10.1002/mrm.20071.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Diffusion tensor imaging (DTI) is known to have a limited capability of resolving multiple fiber orientations within one voxel. This is mainly because the probability density function (PDF) for random spin displacement is non-Gaussian in the confining environment of biological tissues and, thus, the modeling of self-diffusion by a second-order tensor breaks down. The statistical property of a non-Gaussian diffusion process is characterized via the higher-order tensor (HOT) coefficients by reconstructing the PDF of the random spin displacement. Those HOT coefficients can be determined by combining a series of complex diffusion-weighted measurements. The signal equation for an MR diffusion experiment was investigated theoretically by generalizing Fick's law to a higher-order partial differential equation (PDE) obtained via Kramers-Moyal expansion. A relationship has been derived between the HOT coefficients of the PDE and the higher-order cumulants of the random spin displacement. Monte-Carlo simulations of diffusion in a restricted environment with different geometrical shapes were performed, and the strengths and weaknesses of both HOT and established diffusion analysis techniques were investigated. The generalized diffusion tensor formalism is capable of accurately resolving the underlying spin displacement for complex geometrical structures, of which neither conventional DTI nor diffusion-weighted imaging at high angular resolution (HARD) is capable. The HOT method helps illuminate some of the restrictions that are characteristic of these other methods. Furthermore, a direct relationship between HOT and q-space is also established. Magn Reson Med 51:924-937, 2004. (C) 2004 Wiley-Liss, Inc.
Keyword:
magnetic resonance imaging
diffusion
diffusion tensor imaging
high angular resolution
fiber
probability density function
cumulants
期刊
IF:
3
论文数:
1.2W
被引数:
3.1W
机构
暂无机构信息
引用论文
Naturally sourced hydrogels: emerging fundamental materials for next-generation healthcare sensing天然来源的水凝胶: 下一代医疗保健传感的新兴基础材料
PREAI
分享收藏DIFFUSION-WEIGHTED MR IMAGING OF ANISOTROPIC WATER DIFFUSION IN CAT CENTRAL-NERVOUS-SYSTEM.png)
RADIOLOGY
RADIOLOGYIF15.2
PREAI
分享收藏Highly stable Zn anodes realized by 3D zincophilic and hydrophobic interphase buffer layer通过3D zincophilic和疏水性相间缓冲层实现的高度稳定的Zn阳极OAAI
OAAI分享收藏
分享收藏分享收藏
查看更多内容