在编辑的MRS中识别异声回声,使用相循环逆转
Zahra Shams1, Abdelrahman Gad1, Aaron T Gudmundson2
1The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
阶段周期逆转 (PCI) 识别了磁共振成像中不需要的外声 (OOV) 信号的来源. 根据PCI发现优化粉碎机梯度可以提高光谱质量,而无需额外的数据采集.
科学领域:
- 磁共振成像 (MRI) 是一种磁共振成像技术.
- 频谱学是一种光谱学.
- 信号处理 信号处理
背景情况:
- 在MRI中,声外信号 (OOV) 可以使光谱分析复杂化.
- 了解OOV信号的来源对于提高数据质量至关重要.
- 一致传输路径 (CTP) 形式主义为分析信号来源提供了一个框架.
研究的目的:
- 使用CTP形式主义识别OOV信号的来源.
- 从获取阶段循环方案中利用信号阶段信息.
- 为了使OOV信号抑制能够优化粉碎机梯度.
主要方法:
- 引入阶段周期逆转 (PCI) 来识别OOV信号.
- PCI删除和替换接收器阶段以匹配不需要的CTP.
- 在模拟,幻影和体内实验中使用MEGA编辑的PRESS序列验证的PCI.
主要成果:
- 模拟显示PCI完全分离了来自不同CTP的信号.
- 在幻影和体内研究中,PCI确定了负责OOV信号的CTP.
- 基于PCI的优化梯度方案导致志愿者的光谱更清洁.
结论:
- PCI是一种灵活和可通用的方法,用于诊断OOV信号来源.
- 这种方法有助于优化MRI采集参数.
- 这种技术可以应用于各种脉冲序列和voxel位置.
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