Structure Prior Constrained Estimation of Human Cardiac Diffusion Tensors
Structure Prior Constrained Estimation of Human Cardiac Diffusion Tensors
复制标题
人体心脏扩散张量的结构先验约束估计
DOI：
10.1109/tbme.2019.2902381
复制
发表时间：
2019
影响因子：
4.6
通讯作者：
Zhu Yue-Min
中科院分区：
文献类型：
--
作者：
Chu Chun-Yu;Sun Chang-Yu;Kuai Zi-Xiang;Yang Feng;Zhu Yue-Min
目的：本文的目的是提高在具有少数扩散梯度方向的扩散磁共振成像（dMRI）中人体心脏扩散张量（DT）估计的准确性。方法：提出一种结构先验约束（SPC）方法。该方法是在传统的非线性最小二乘估计器中引入两个正则化子。这两个正则化惩罚相邻DT之间的不相似性和估计的和先前的纤维方向之间的差异，分别。给出了一种新的数值解法，保证了估计的正定性。结果如下：在离体心脏数据上的实验表明，SPC方法能够很好地估计大多数体素的DT，并且在主特征向量、次特征向量、螺旋角、横向角、分数各向异性和平均扩散率的平均误差方面优于现有方法上级。结论：SPC方法是一种实用和可靠的替代目前的去噪或正则化为基础的方法，用于估计人类心脏DT。意义：SPC方法能够准确估计具有少数扩散梯度方向的dMRI中的人类心脏DT。
Objective: The purpose of this paper is to increase the accuracy of human cardiac diffusion tensor (DT) estimation in diffusion magnetic resonance imaging (dMRI) with a few diffusion gradient directions. Methods: A structure prior constrained (SPC) method is proposed. The method consists in introducing two regularizers in the conventional nonlinear least squares estimator. The two regularizers penalize the dissimilarity between neighboring DTs and the difference between estimated and prior fiber orientations, respectively. A novel numerical solution is presented to ensure the positive definite estimation. Results: Experiments on ex vivo human cardiac data show that the SPC method is able to well estimate DTs at most voxels, and is superior to state-of-the-art methods in terms of the mean errors of principal eigenvector, second eigenvector, helix angle, transverse angle, fractional anisotropy, and mean diffusivity. Conclusion: The SPC method is a practical and reliable alternative to current denoising- or regularization-based methods for the estimation of human cardiac DT. Significance: The SPC method is able to accurately estimate human cardiac DTs in dMRI with a few diffusion gradient directions.