English

Artifact Correction for Echo-Planar Imaging at Low-Field and Ultra-Low-Field MRI

Computer Vision and Pattern Recognition 2026-05-26 v1

Abstract

Purpose: Echo-planar imaging (EPI) in low-field (LF) and ultra-low-field MRI (ULF) suffers from severe Nyquist ghost artifacts due to odd-even k-space misalignment. This study develops a reference-free artifact correction pipeline that reduces reliance on conventional reference scans while achieving improved ghost suppression. Methods: Starting from the traditional reference-scan-based ghost artifact correction method, we first introduce a peak-alignment-based ghost artifact correction method to correct odd-even line displacement without reference data. To further reduce residual artifacts, an interpolation-and-resampling strategy is applied. The combined method was evaluated using EPI and diffusion-weighted EPI data in LF and ULF. Results: The proposed pipeline effectively mitigated Nyquist ghosts, improved structural continuity, and enhanced signal uniformity. Peak-alignment-based ghost artifact correction method alone provided comparable artifact suppression to reference-scan-based ghost artifact correction method, while interpolation and resampling further suppressed residual artifacts, enabling reliable visualization of brain structures under ULF conditions. Conclusion: A practical, reference-free correction pipeline is presented for LF and ULF EPI, combining peak-alignment-based ghost artifact correction method and interpolation-resampling to achieve efficient ghost suppression and expand the clinical applicability of low-field MRI systems, providing both theoretical guidance and practical experience for ULF EPI-based DWI imaging.

Keywords

Cite

@article{arxiv.2605.25589,
  title  = {Artifact Correction for Echo-Planar Imaging at Low-Field and Ultra-Low-Field MRI},
  author = {Sisi Qiao and Yilin Yu and Tiecheng Lin and Yuhao Liu and Jiajia Sun and Xiaoling Li},
  journal= {arXiv preprint arXiv:2605.25589},
  year   = {2026}
}

Comments

19 pages, 10 figures, 2 tables