Beyond traditional Magnetic Resonance processing with Artificial Intelligence
<|reference_start|>Beyond traditional Magnetic Resonance processing with Artificial Intelligence: 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.<|reference_end|>
@article{jahangiri2024beyond,
    title={Beyond traditional Magnetic Resonance processing with Artificial
  Intelligence},
    author={Amir Jahangiri and Vladislav Orekhov (Department of Chemistry and
  Molecular Biology, Swedish NMR Centre, University of Gothenburg, Sweden)},
    journal={arXiv preprint arXiv:2405.07657},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.07657},
    primaryClass={physics.bio-ph cs.LG eess.SP}
}