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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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相关实验视频

Updated: Jun 19, 2025

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods
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深度学习用于加速和强大的MRI重建.

Reinhard Heckel1, Mathews Jacob2, Akshay Chaudhari3,4

  • 1Department of computer engineering, Technical University of Munich, Munich, Germany.

Magma (New York, N.Y.)
|July 23, 2024
PubMed
概括
此摘要是机器生成的。

深度学习 (DL) 通过提高图像质量和扫描速度,显著增强磁共振成像 (MRI) 重建. 本综述涵盖了DL方法,解决临床放射学的局限性和未来潜力.

关键词:
深度学习是一种深度学习.图像重建 图像重建这就是为什么MRI是MRI.机器学习是机器学习.

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Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
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相关实验视频

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科学领域:

  • 放射学 放射学是一门学科.
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 磁共振成像 (MRI) 对于诊断放射学至关重要.
  • 传统的MRI重建在图像质量和扫描时间方面面临限制.
  • 深度学习 (DL) 为MRI提供了变革的潜力.

研究的目的:

  • 提供对MRI重建的DL近期进展的全面审查.
  • 探索MRI增强的各种DL方法和架构.
  • 突出DL在克服传统MRI局限性的作用.

主要方法:

  • 对端到端神经网络,预训练模型和生成模型的审查.
  • 对MRI重建的自主监督DL方法的分析.
  • 讨论DL用于优化采集协议和应对数据挑战.

主要成果:

  • DL可以提高MRI图像质量,加快扫描时间.
  • DL方法解决了诸如分配转移和偏差等挑战.
  • 各种DL架构对MRI重建有显著的贡献.

结论:

  • DL是一个关键的技术,彻底改变了MRI重建.
  • DL有可能对临床成像实践产生重大影响.
  • 未来的研究方向重点是进一步利用MRI中的DL.