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MR-zero与RARE MRI相结合:联合优化重定焦翻转角度和神经网络,以最大限度地减少T2 - - 在旋回回声序列中引起的模糊
Hoai Nam Dang1, Jonathan Endres1, Simon Weinmüller1
1Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
Magnetic resonance in medicine
|June 26, 2023
概括
这项研究引入了一种结合优化翻转角度和神经网络的新方法,以显著减少T2诱导的模糊在快速成像中与重定焦回声 (RARE) MRI序列.
科学领域:
- 磁共振成像 (MRI) 是一种磁共振成像技术.
- 医学物理 医学物理
- 计算成像技术的成像
背景情况:
- 在一次性快速成像中,T2诱导的模糊会降低图像质量,并重新聚焦回声 (RARE) 序列.
- 优化脉冲序列对于提高MRI性能至关重要.
研究的目的:
- 开发一个端到端可微分的2D布洛赫模拟,以减少T2诱导的模糊在单次射击RARE序列.
- 为了共同优化重定焦翻转角度和卷积神经网络 (CNN),以提高图像清晰度和对比度.
主要方法:
- 使用MR-zero框架进行模拟和优化.
- 联合优化了可变翻转角列车和使用瞬间横向磁化作为目标的DenseNet参数.
- 在使用Pulseq标准的3T西门子PRISMA系统上验证了优化序列.
主要成果:
- 在质子密度加权和T2加权单拍RARE图像中成功减少T2诱导的模糊.
- 使用CNN实现了增强的图像清晰度和更正的对比度变化.
- 与现有方法相比,通过视觉检查和点传播功能分析,表现出更好的性能.
结论:
- 可变翻转角度和CNN的联合端到端优化能够更有效地减少T2引起的模糊.
- 这种方法促进了更快的RAREMRI,用于单次和多次拍摄的扩展回声列车.
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