FCG is an effective and robust method for correcting spatiotemporal phase errors in EPI, enabling improved image quality on high-performance systems.
Abstract
Purpose To develop a Field-Correcting GRAPPA (FCG) technique to correct the spatiotemporal-varying phase errors in EPI caused by eddy currents. Methods The fast-changing gradient in EPI causes strong eddy current effects and associated spatiotemporal-varying phase errors, producing significant image artifacts. The use of higher gradient amplitude, slew rate, and ramp sampling factor for faster imaging exacerbates this problem. In this work, FCG was developed to address this challenge by using a multi-layer perceptron (MLP) to provide a compact representation of a family of GRAPPA-like kernels that correct the spatiotemporal-varying phase errors in the data. A dedicated calibration pipeline was designed to acquire high-quality source and target data for MLP training in both slice-by-slice and simultaneous multi-slice (SMS) acquisitions. To validate FCG’s assumptions and performance, a field camera was used to provide ground-truth measurement of phase patterns. The performance of FCG was further validated on phantom and in vivo experiments using demanding EPI trajectories across multiple 3T and 7T systems. Results Field camera measurements revealed strong spatiotemporal phase variations along the kx direction that repeat along ky during EPI readouts. The experiments on high-performance systems across 3T and 7T demonstrate that FCG can provide superior correction for the artifacts induced by spatiotemporal-varying phase errors compared with existing approaches. Conclusion FCG is an effective and robust method for correcting spatiotemporal phase errors in EPI, enabling improved image quality on high-performance systems.
PURPOSE
The alternating unbalanced SSFP (AUSFIDE) pulse sequence, which consists of multi-echo trains of SSFP-FID and SSFP-ECHO modules, enables rapid estimation of R2 and R2', but is prone to errors from temporal drift of the main magnetic field (B0) and k-space trajectory mismatch. Here, we propose a self-correcting...
Eunseo Bae, Sung Suk Oh, Dongyeob Han et al.· Magnetic Resonance in Medici...· 0 citations
Purpose: Although image reconstruction has received relatively little attention in ASL research to date, it has the potential to address several challenges in ASL. As well as speeding up measurements by increasing undersampling and reducing measurement artifacts, it can improve the signal-to-noise ratio (SNR) of a give...
Ingmar Sorgenfrei, Qin-Yang Shou, Ingrid Barth et al.· arXiv.org· 0 citations
Subject motion and gradient heating-induced frequency and phase offsets result in spectral misalignment during single-voxel MR spectroscopy (SVS) acquisitions. Several methods have been presented to align the spectra, but their performance on a 7T system is unclear. This study aimed to evaluate the practical importance...
Chu-Yu Lee, Jia Xu, Bao-Lian Yang et al.· bioRxiv· 0 citations
Abstract.
Parallel Magnetic Resonance Imaging (pMRI) shortens scan time by reducing the amount of k-space data acquired from multiple receiver coils. Conventional model-based reconstruction algorithms typically exploit either coil sensitivity information in the image domain or intercoil correlations in the frequency d...
Wei-Peng Chen, Hong-Jia Chen, Yan-Ran Li et al.· SIAM Journal of Imaging Scie...· 0 citations
This work presents a new B1 + and B1 - model-based fitting approach for interferometric presaturated TurboFLASH data, which improves B1 + and B1 - mapping robustness to noise and enables more flexible satTFL acquisition scheme, allowing better trade-offs between accuracy and scan time.
Natalia Dudysheva, Franck Mauconduit, Michel Luong et al.· Magnetic Resonance in Medici...· 0 citations
BACKGROUND/PURPOSE
Simultaneous T1/T2 mapping with hybrid (mixed) sequences has been proposed, but clinical use is limited by long acquisition times. Accelerated reconstruction-parallel imaging (PI; SENSE), compressed sensing (CS), and deep learning (DL)-allows shorter scans but may alter quantitative values and image...
M. Kanamoto, Yuki Matta, Toshiki Tateishi et al.· Magnetic Resonance Imaging· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.