Nonlinear regularization for per voxel estimation of magnetic susceptibility distributions from MRI field maps.
Nonlinear regularization for per voxel estimation of magnetic susceptibility distributions from MRI field maps.
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DOI：
10.1109/tmi.2009.2023787
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发表时间：
2010-02
影响因子：
10.6
通讯作者：
Wang Y
中科院分区：
文献类型：
--
作者：
Kressler B;de Rochefort L;Liu T;Spincemaille P;Jiang Q;Wang Y
磁化率是组织的一种重要物理性质，可作为磁共振成像中的一种对比机制。最近，通过与信号分子偶联靶向造影剂和用造影剂标记干细胞已经成为可能。这些造影剂具有很强的顺磁性，量化磁化率的能力可以准确测量信号和细胞定位。本文提出了一种通过从核磁共振扫描仪获得的场图求解不适定逆问题来估计任意磁化率分布的技术。考虑了两种正则化策略，一种是传统的Tikhonov正则化，另一种是基于ℓ-1范数的稀疏性推广的非线性正则化。概念验证是使用数值模拟、幻影和在中风模型小鼠中进行的。初步经验表明，非线性正则化较好地抑制了磁化率估计中常见的噪声和条纹伪影。
Magnetic susceptibility is an important physical property of tissues, and can be used as a contrast mechanism in magnetic resonance imaging. Recently, targeting contrast agents by conjugation with signaling molecules and labeling stem cells with contrast agents have become feasible. These contrast agents are strongly paramagnetic, and the ability to quantify magnetic susceptibility could allow accurate measurement of signaling and cell localization. Presented here is a technique to estimate arbitrary magnetic susceptibility distributions by solving an ill-posed inversion problem from field maps obtained in an MRI scanner. Two regularization strategies are considered, conventional Tikhonov regularization, and a sparsity promoting nonlinear regularization using the ℓ1 norm. Proof of concept is demonstrated using numerical simulations, phantoms, and in a stroke model mouse. Initial experience indicates that the nonlinear regularization better suppresses noise and streaking artifacts common in susceptibility estimation.