A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements
A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements
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DOI：
10.1002/jmri.10350
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发表时间：
2003-08-01
影响因子：
4.4
通讯作者：
Wheeler-Kingshott, CAM
中科院分区：
文献类型：
--
作者：
Parker, GJM;Haroon, HA;Wheeler-Kingshott, CAM
目的：要建立一个通用的方法来量化基于流线的扩散纤维跟踪方法在点和/或regions.Materials和方法之间的连接的概率：常用的流线的方法是适应于利用的不确定性的扩散定义为每个图像体素的主要方向的方向。使用蒙特卡罗方法重复运行流线过程以利用这种固有的不确定性，从而生成连接概率图。不确定性是通过解释扩散张量提供的扩散取向轮廓的形状在底层microstructure.Results的定义：两个候选人描述的不确定性的扩散张量提出和地图的概率连接到选定的起始点或区域中产生的一些主要tracts.Conclusion：所提出的方法提供了一个通用的框架，利用流线的方法来生成概率图的连接。
Purpose: To establish a general methodology for quantifying streamline-based diffusion fiber tracking methods in terms of probability of connection between points and/or regions.Materials and Methods: The commonly used streamline approach is adapted to exploit the uncertainty in the orientation of the principal direction of diffusion defined for each image voxel. Running the streamline process repeatedly using Monte Carlo methods to exploit this inherent uncertainty generates maps of connection probability. Uncertainty is defined by interpreting the shape of the diffusion orientation profile provided by the diffusion tensor in terms of the underlying microstructure.Results: Two candidates for describing the uncertainty in the diffusion tensor are proposed and maps of probability of connection to chosen start points or regions are generated in a number of major tracts.Conclusion: The methods presented provide a generic framework for utilizing streamline methods to generate probabilistic maps of connectivity.