Björk Marcus, Ingle R Reeve, Gudmundson Erik, Stoica Petre, Nishimura Dwight G, Barral Joëlle K
Department of Information Technology, Uppsala University, Uppsala, Sweden.
Magn Reson Med. 2014 Sep;72(3):880-92. doi: 10.1002/mrm.24986. Epub 2013 Oct 25.
The balanced steady-state free precession (bSSFP) pulse sequence has shown to be of great interest due to its high signal-to-noise ratio efficiency. However, bSSFP images often suffer from banding artifacts due to off-resonance effects, which we aim to minimize in this article.
We present a general and fast two-step algorithm for 1) estimating the unknowns in the bSSFP signal model from multiple phase-cycled acquisitions, and 2) reconstructing band-free images. The first step, linearization for off-resonance estimation (LORE), solves the nonlinear problem approximately by a robust linear approach. The second step applies a Gauss-Newton algorithm, initialized by LORE, to minimize the nonlinear least squares criterion. We name the full algorithm LORE-GN.
We derive the Cramér-Rao bound, a theoretical lower bound of the variance for any unbiased estimator, and show that LORE-GN is statistically efficient. Furthermore, we show that simultaneous estimation of T1 and T2 from phase-cycled bSSFP is difficult, since the Cramér-Rao bound is high at common signal-to-noise ratio. Using simulated, phantom, and in vivo data, we illustrate the band-reduction capabilities of LORE-GN compared to other techniques, such as sum-of-squares.
Using LORE-GN we can successfully minimize banding artifacts in bSSFP.
平衡稳态自由进动（bSSFP）脉冲序列因其高信噪比效率而备受关注。然而，bSSFP图像常常因失谐效应而出现带状伪影，本文旨在将其降至最低。
我们提出了一种通用且快速的两步算法，用于：1）从多个相位循环采集数据中估计bSSFP信号模型中的未知量；2）重建无带状伪影的图像。第一步，失谐估计线性化（LORE），通过一种稳健的线性方法近似求解非线性问题。第二步应用由LORE初始化的高斯 - 牛顿算法，以最小化非线性最小二乘准则。我们将完整算法命名为LORE - GN。
我们推导了克拉美 - 罗界，即任何无偏估计器方差的理论下限，并表明LORE - GN在统计上是有效的。此外，我们表明从相位循环bSSFP中同时估计T1和T2很困难，因为在常见信噪比下克拉美 - 罗界很高。使用模拟、体模和体内数据，我们展示了与其他技术（如平方和技术）相比，LORE - GN减少带状伪影的能力。
使用LORE - GN我们能够成功地将bSSFP中的带状伪影降至最低。
