Quantitative Susceptibility Mapping Using Structural Feature Based Collaborative Reconstruction (SFCR) in the Human Brain
Quantitative Susceptibility Mapping Using Structural Feature Based Collaborative Reconstruction (SFCR) in the Human Brain
复制标题
使用人脑中基于结构特征的协作重建 (SFCR) 进行定量敏感性绘图
DOI：
10.1109/tmi.2016.2544958
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发表时间：
2016-09-01
影响因子：
10.6
通讯作者：
van Zijl, Peter C. M.
中科院分区：
文献类型：
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作者：
Bao, Lijun;Li, Xu;van Zijl, Peter C. M.
从局部相位测量重建MR定量磁化率图（QSM）是一个不适定的逆问题，不同的正则化策略，结合从幅度和相位图像提取的先验信息已被提出。然而，在幅度和相位图像中观察到的解剖结构并不总是与磁化率图中的解剖结构在空间上一致，这可能在重建的磁化率图中给出错误的估计。在本文中，我们开发了一种基于结构特征的协作重建（SFCR）方法QSM包括幅度和磁化率的信息。SFCR算法由两个连续的步骤组成，对应于互补的重建模型，每个步骤都具有基于结构特征的l1范数约束和基于体素保真度的l2范数约束，这使得结构边缘和微小特征都可以恢复，而噪声和伪影可以减少。在M-步骤中，通过采用基于k-空间的压缩感知模型并结合幅度先验来重建初始磁化率图。在S步骤中，使用从M步骤的初始磁化率图导出的加权约束在空间域中拟合磁化率图。在7 T MRI上的仿真和体内人体实验表明，SFCR方法提供了高质量的磁化率图，具有改进的RMSE和MSSIM。最后，在多个头部位置下分析了深部灰质的磁化率值，其中仰卧位最接近金标准COSMOS结果。
The reconstruction of MR quantitative susceptibility mapping (QSM) from local phase measurements is an ill posed inverse problem and different regularization strategies incorporating a priori information extracted from magnitude and phase images have been proposed. However, the anatomy observed in magnitude and phase images does not always coincide spatially with that in susceptibility maps, which could give erroneous estimation in the reconstructed susceptibility map. In this paper, we develop a structural feature based collaborative reconstruction (SFCR) method for QSM including both magnitude and susceptibility based information. The SFCR algorithm is composed of two consecutive steps corresponding to complementary reconstruction models, each with a structural feature based l 1 norm constraint and a voxel fidelity based l 2 norm constraint, which allows both the structure edges and tiny features to be recovered, whereas the noise and artifacts could be reduced. In the M-step, the initial susceptibility map is reconstructed by employing a k-space based compressed sensing model incorporating magnitude prior. In the S-step, the susceptibility map is fitted in spatial domain using weighted constraints derived from the initial susceptibility map from the M-step. Simulations and in vivo human experiments at 7T MRI show that the SFCR method provides high quality susceptibility maps with improved RMSE and MSSIM. Finally, the susceptibility values of deep gray matter are analyzed in multiple head positions, with the supine position most approximate to the gold standard COSMOS result.