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相关概念视频

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Atomic Nuclei: Magnetic Resonance01:05

Atomic Nuclei: Magnetic Resonance

636
The number of nuclear spins aligned in the lower energy state is slightly greater than those in the higher energy state. In the presence of an external magnetic field, as the spins precess at the Larmor frequency, the excess population results in a net magnetization oriented along the z axis. When a pulse or a short burst of radio waves at the Larmor frequency is applied along the x axis, the coupling of frequencies causes resonance and flips the nuclear spins of the excess population from the...
636
Applications Of NMR In Biology01:25

Applications Of NMR In Biology

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Nuclear magnetic resonance (NMR) spectroscopy is a very valuable analytical technique for researchers. It has been used for more than 50 years as an analytical tool. F. Bloch and E. Purcell formulated NMR in 1946 and won the 1952 Nobel Prize in Physics  for their work. Biological macromolecules such as proteins, nucleic acids, lipids, and organic molecules including pharmaceutical compounds, can be studied using this versatile tool that exploits the magnetic properties of certain nuclei.
3.7K
Nuclear Magnetic Resonance (NMR): Overview01:07

Nuclear Magnetic Resonance (NMR): Overview

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Nuclear magnetic resonance (NMR) is a phenomenon exhibited by certain nuclei that can absorb characteristic radio frequency radiation under certain conditions. NMR has been extensively applied in molecular spectroscopy and medical diagnostic imaging. In both these applications, the molecule or subject under study is placed in a magnetic field and irradiated with radio frequency energy.
NMR spectroscopy generates a spectrum where the characteristic absorption frequencies of the sample are...
2.2K
NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

675
When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
675
Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

191
Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...
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相关实验视频

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Quantifying Mixing using Magnetic Resonance Imaging
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超越传统的磁共振处理与人工智能的人工智能处理.

Amir Jahangiri1, Vladislav Orekhov2

  • 1Department of Chemistry and Molecular Biology, Swedish NMR Centre, University of Gothenburg, Gothenburg, 40530, Sweden.

Communications chemistry
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概括
此摘要是机器生成的。

人工智能 (AI) 通过实现不可能的任务来推进核磁共振 (NMR). 人工智能为四边形检测,信号强度不确定性评估和NMR频谱质量评分提供了新方法.

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科学领域:

  • 核磁共振 (NMR) 光谱学是指核磁共振 (NMR) 的光谱学.
  • 人工智能 (AI) 在科学仪器仪表中的应用

背景情况:

  • 传统的NMR信号处理面临着局限性.
  • 人工智能正在成为增强NMR应用的强大工具.

研究的目的:

  • 为了证明AI能够在NMR中解决以前难以解决的问题.
  • 开发用于NMR数据分析的新型AI驱动的方法.

主要方法:

  • 人工神经网络 (ANN) 的开发和培训.
  • 应用ANNs来解决特定的NMR处理挑战.

主要成果:

  • 仅使用回声/反回声调制,实现了正方形检测.
  • 开发了一种方法来量化每个光谱点的信号强度不确定性.
  • 为评估NMR频谱质量创建了一个无参考分数.

结论:

  • 人工智能技术比传统的NMR处理提供了显著的进步.
  • 人工智能有可能彻底改变NMR数据分析和解释.