无需参考扫描,就能有效消除低场MRI的伪影,提升成像质量。
Artifact Correction for Echo-Planar Imaging at Low-Field and Ultra-Low-Field MRI
- 基于峰值对齐法修正奇偶行错位,无需参考数据。
- 结合插值重采样进一步抑制残留伪影,脑结构清晰可见。
- 适合低场和超低场MRI临床应用,尤其利于扩散成像。
低场(LF)和超低场(ULF)磁共振成像中的回波平面成像(EPI)因奇偶k-space线错位,产生严重尼奎斯特伪影。本文提出一种无参考数据的伪影校正流程:首先采用基于峰值对齐的校正方法,无需参考扫描即可修正奇偶行位移;随后引入插值与重采样策略,进一步降低残余伪影。该方法在LF和ULF的EPI及扩散加权EPI数据上验证,有效缓解了伪影,改善了结构连续性与信号均匀性。仅峰值对齐法即达到与传统参考扫描法相当的伪影抑制效果,结合插值重采样后,可实现超低场下可靠脑部结构可视化。本研究为低场与超低场EPI的扩散成像提供了实用、无需参考扫描的校正方案,兼具理论指导与临床应用价值。
原文摘要 · Abstract (English)
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.
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