Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, USA.
Magn Reson Med. 2021 Nov;86(5):2733-2750. doi: 10.1002/mrm.28830. Epub 2021 Jul 5.
To investigate and remove Gibbs-ringing artifacts caused by partial Fourier (PF) acquisition and zero filling interpolation in MRI data.
Gibbs ringing of fully sampled data, leading to oscillations around tissue boundaries, is caused by the symmetric truncation of k-space. Such ringing can be removed by conventional methods, with the local subvoxel shifts method being the state-of-the-art. However, the asymmetric truncation of k-space in routinely used PF acquisitions leads to additional ringings of wider intervals in the PF sampling dimension that cannot be corrected solely based on magnitude images reconstructed via zero filling. Here, we develop a pipeline for the Removal of PF-induced Gibbs ringing (RPG) to remove ringing patterns of different periods by applying the conventional method twice. The proposed pipeline is validated on numerical phantoms, demonstrated on in vivo diffusion MRI measurements, and compared with the conventional method and neural network-based approach.
For PF = 7/8 and 6/8, Gibbs-ringings and subsequent bias in diffusion metrics induced by PF acquisition and zero filling are robustly removed by using the proposed RPG pipeline. For PF = 5/8, however, ringing removal via RPG leads to excessive image blurring due to the interplay of image phase and convolution kernel.
RPG corrects Gibbs-ringing artifacts in magnitude images of PF acquired data and reduces the bias in quantitative MR metrics. Considering the benefit of PF acquisition and the feasibility of ringing removal, we suggest applying PF = 6/8 when PF acquisition is necessary.
研究并消除磁共振成像(MRI)数据中部分傅里叶(PF)采集和零填充插值引起的 Gibbs 振铃伪影。
完全采样数据的 Gibbs 振铃会导致组织边界周围的波动,这是由于 k 空间的对称截断引起的。这种振铃可以通过传统方法去除,其中局部亚像素移位方法是最先进的方法。然而,在常规使用的 PF 采集中,k 空间的非对称截断会导致在 PF 采样维度中出现更宽间隔的附加振铃,这些振铃不能仅基于通过零填充重建的幅度图像来纠正。在这里,我们开发了一种用于去除 PF 引起的 Gibbs 振铃(RPG)的流水线,通过两次应用传统方法来去除不同周期的振铃模式。该流水线在数值体模上进行了验证,在体内扩散 MRI 测量中进行了演示,并与传统方法和基于神经网络的方法进行了比较。
对于 PF = 7/8 和 6/8,通过使用所提出的 RPG 流水线,可以可靠地去除 PF 采集和零填充引起的 Gibbs 振铃和随后的扩散度量偏差。然而,对于 PF = 5/8,由于图像相位和卷积核的相互作用,通过 RPG 去除振铃会导致过度的图像模糊。
RPG 纠正了 PF 采集数据的幅度图像中的 Gibbs 振铃伪影,并降低了定量 MR 度量的偏差。考虑到 PF 采集的益处和振铃去除的可行性,我们建议在需要 PF 采集时应用 PF = 6/8。