Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

8.9K
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...
8.9K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Dynamic behavior of the nucleus pulposus within the intervertebral disc loading: a systematic review and meta-analysis exploring the concept of dynamic disc model.

Frontiers in bioengineering and biotechnology·2025
Same author

MRI at low field: A review of software solutions for improving SNR.

NMR in biomedicine·2024
Same author

ESMRMB 2024 focus topic: MR beyond trends-fact-checking MR.

Magma (New York, N.Y.)·2024
Same author

Quantitative imaging through the production chain: from idea to application.

Magma (New York, N.Y.)·2023
Same author

Editorial: Innovations in MR hardware from ultra-low to ultra-high field.

Frontiers in physics·2023
Same author

Exploring the foothills: benefits below 1 Tesla?

Magma (New York, N.Y.)·2023

相关实验视频

Updated: Jan 7, 2026

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases
09:55

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Published on: January 5, 2024

1.7K

基于深度学习的快速零射击无光化方法用于低场MR图像.

Reina Ayde1,2, Gabriel Zihlmann3, Najat Salameh3

  • 1Center for Adaptable MRI Technology, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, UK. reina.ayde@gmail.com.

Magma (New York, N.Y.)
|December 22, 2025
PubMed
概括

这项研究优化了低场MRI的零射击消光方法,显著加快了训练时间,改善了临床诊断的图像质量. 这种方法通过减少噪声而提高诊断准确性,而无需先前的数据要求.

关键词:
深度学习是一种深度学习.拒绝这种行为是拒绝的.低电场的低电场.这就是为什么MRI是MRI.自主监督的自我监督这是一次零射击.

更多相关视频

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.3K
Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research
08:33

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

1.6K

相关实验视频

Last Updated: Jan 7, 2026

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases
09:55

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Published on: January 5, 2024

1.7K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.3K
Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research
08:33

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

1.6K

科学领域:

  • 医疗成像医学成像
  • 磁共振成像 (MRI) 是一种磁共振成像技术.
  • 图像处理 图像处理

背景情况:

  • 低场MRI对于可访问的诊断至关重要,但通常会受到图像噪声的影响,影响临床效用.
  • 传统的脱光方法需要大量的训练数据,这对于低场MRI来说具有挑战性.
  • 零射击自主监督学习提供了一个有希望的替代方案,因为它消除了对先前培训数据的需求.

研究的目的:

  • 适应和优化低场MRI的零射击消噪方法.
  • 为了加快扫描特定的无雾化方法的培训过程.
  • 为了提高低场MRI的图像质量,以提高临床诊断.

主要方法:

  • 扩展了零射击噪声清洁 (ZS-NAC) 方法,并对更快的训练进行了修改.
  • 将拟议的方法与BM4D和零射击噪声2噪声技术进行了比较.
  • 对高场数据进行定量评估,对预期低场 (0.1 T) 数据进行定性评估.
  • 在部分数据矩阵上进行了研究培训,以进一步加速.

主要成果:

  • 优化的 ZS-NAC 方法在各种信号噪声比 (SNR) 级别中实现了高无噪声性能.
  • 对于典型的低场MRI数据尺寸,在GPU上观察到快速处理时间 (秒).
  • 对数据子集的培训表明了培训显著加速的潜力.

结论:

  • 开发的除方法显示了无集成到低场MRI采集工作流程的巨大潜力.
  • 这种方法可以有效地提高图像质量,帮助临床诊断.
  • 该方法的效率和适应性使其适合于现实世界的临床应用.