Uecker Martin, Hohage Thorsten, Block Kai Tobias, Frahm Jens
Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen, Germany.
Magn Reson Med. 2008 Sep;60(3):674-82. doi: 10.1002/mrm.21691.
The use of parallel imaging for scan time reduction in MRI faces problems with image degradation when using GRAPPA or SENSE for high acceleration factors. Although an inherent loss of SNR in parallel MRI is inevitable due to the reduced measurement time, the sensitivity to image artifacts that result from severe undersampling can be ameliorated by alternative reconstruction methods. While the introduction of GRAPPA and SENSE extended MRI reconstructions from a simple unitary transformation (Fourier transform) to the inversion of an ill-conditioned linear system, the next logical step is the use of a nonlinear inversion. Here, a respective algorithm based on a Newton-type method with appropriate regularization terms is demonstrated to improve the performance of autocalibrating parallel MRI--mainly due to a better estimation of the coil sensitivity profiles. The approach yields images with considerably reduced artifacts for high acceleration factors and/or a low number of reference lines.
在MRI中使用并行成像来减少扫描时间时，当使用GRAPPA或SENSE进行高加速因子成像时会面临图像质量下降的问题。尽管由于测量时间减少，并行MRI中SNR的固有损失不可避免，但通过替代重建方法可以改善对严重欠采样导致的图像伪影的敏感性。虽然GRAPPA和SENSE的引入将MRI重建从简单的酉变换（傅里叶变换）扩展到病态线性系统的反演，但下一个合理步骤是使用非线性反演。在此，展示了一种基于带有适当正则化项的牛顿型方法的相应算法，以提高自动校准并行MRI的性能——主要是由于对线圈灵敏度分布有更好的估计。该方法对于高加速因子和/或少量参考线能产生伪影显著减少的图像。
