Smart signal processing approaches using Artificial Intelligence are gaining
momentum in NMR applications. In this study, we demonstrate that AI offers new
opportunities beyond tasks addressed by traditional techniques. We developed
and trained several artificial neural networks in our new toolbox Magnetic
Resonance with Artificial intelligence (MR-Ai) to solve three "impossible"
problems: quadrature detection using only Echo (or Anti-Echo) modulation from
the traditional Echo/Anti-Echo scheme; accessing uncertainty of signal
intensity at each point in a spectrum processed by any given method; and
defining a reference-free score for quantitative access of NMR spectrum
quality. Our findings highlight the potential of AI techniques to revolutionize
NMR processing and analysis.

通过使用人工智能的智能信号处理方法，我们展示了人工智能在核磁共振应用中超越传统技术的新机遇。我们开发和训练了几个人工神经网络，应用在我们的新工具箱 MR-Ai 中，解决了三个 “不可能” 的问题：仅使用传统 Echo/Anti-Echo 方案中 Echo（或 Anti-Echo）调制进行象限检测；获取由任何给定方法处理的光谱中每个点信号强度的不确定性；以及定义一个无需参考的评分来定量评估核磁共振光谱质量。我们的发现突显了人工智能技术改变核磁共振处理和分析的潜力。