Sun Chang-Yu, Zhu Yue-Min, Chu Chun-Yu, Yang Feng, Liu Wan-Yu, Korenberg Julie R, Hsu Edward W
CREATIS, CNRS UMR 5220, Inserm U1044, INSA Lyon, University of Lyon, Villeurbanne, France.
Harbin Institute of Technology, Harbin, China.
PLoS One. 2016 Feb 26;11(2):e0150161. doi: 10.1371/journal.pone.0150161. eCollection 2016.
Orientation distribution functions (ODFs) are widely used to resolve fiber crossing problems in high angular resolution diffusion imaging (HARDI). The characteristics of the ODFs are often assessed using a visual criterion, although the use of objective criteria is also reported, which are directly borrowed from classic signal and image processing theory because they are intuitive and simple to compute. However, they are not always pertinent for the characterization of ODFs. We propose a more general paradigm for assessing the characteristics of ODFs. The idea consists in regarding an ODF as a three-dimensional (3D) point cloud, projecting the 3D point cloud onto an angle-distance map, constructing an angle-distance matrix, and calculating metrics such as length ratio, separability, and uncertainty. The results from both simulated and real data show that the proposed metrics allow for the assessment of the characteristics of ODFs in a quantitative and relatively complete manner.
取向分布函数（ODFs）在高角分辨率扩散成像（HARDI）中被广泛用于解决纤维交叉问题。尽管也有报道使用从经典信号和图像处理理论直接借鉴而来的客观标准来评估ODFs的特征，因为这些标准直观且计算简单，但ODFs的特征通常还是使用视觉标准来评估。然而，它们并不总是适用于ODFs的特征描述。我们提出了一种更通用的范式来评估ODFs的特征。其思路是将一个ODF视为一个三维（3D）点云，将3D点云投影到一个角度 - 距离图上，构建一个角度 - 距离矩阵，并计算诸如长度比、可分离性和不确定性等指标。模拟数据和真实数据的结果都表明，所提出的指标能够以定量且相对完整的方式评估ODFs的特征。
