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

5.0K
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...
5.0K

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

Effect of Medicaid coverage of tobacco-dependence treatments on smoking cessation.

International journal of environmental research and public health·2010
Same author

Cytokine and autoantibody patterns in acute liver failure.

Journal of immunotoxicology·2009
Same author

A novel scoring system for prognostic prediction in d-galactosamine/lipopolysaccharide-induced fulminant hepatic failure BALB/c mice.

BMC gastroenterology·2009
Same author

Mammalian target of rapamycin signaling pathway contributes to glioma progression and patients' prognosis.

The Journal of surgical research·2009
Same author

Estrogen receptor neurobiology and its potential for translation into broad spectrum therapeutics for CNS disorders.

Current molecular pharmacology·2009
Same author

Transcriptional and post-translational regulation of adiponectin.

The Biochemical journal·2009

相关实验视频

Updated: Jun 9, 2025

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.4K

复杂值图像重建压缩感应MRI使用等级约束的复杂值图像重建.

Xue Bi1, Xinwen Liu2, Zhifeng Chen3

  • 1School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, China; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia.

Magnetic resonance imaging
|October 25, 2024
PubMed
概括

这项研究引入了一种用于更快的磁共振成像 (MRI) 扫描的新方法,通过同时重建大小和相位图像. 该技术提高了图像质量,并减少了复杂值的MRI重建中的文物.

关键词:
复杂值的MRI是复杂值的压缩感应感应 压缩感应层次上的约束 层次上的约束图像重建的大小图像重建.阶段规范化的阶段规范化.

更多相关视频

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods
05:07

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Published on: September 6, 2024

282
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.6K

相关实验视频

Last Updated: Jun 9, 2025

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.4K
Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods
05:07

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Published on: September 6, 2024

282
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.6K

科学领域:

  • 医疗成像医学成像
  • 信号处理 信号处理
  • 计算科学 计算科学

背景情况:

  • 磁共振成像 (MRI) 扫描时间因顺序 k 空间数据采集而延长.
  • 压缩传感 (CS) 技术低采样k空间数据以加速MRI扫描.
  • 虽然大小图像是优先考虑的,但复杂值MRI中的相位组件对于诊断诸如神经退行性疾病等疾病至关重要.

研究的目的:

  • 开发一种用于复杂值核磁共振 (MRI) 中同时重建大小和相位图像的新方法.
  • 通过利用两个图像组件来增强MRI的诊断效用.
  • 通过先进的压缩传感技术加速MRI采集.

主要方法:

  • 一个基于非亚样本轮变换 (NSCT) 的新算法,用于复杂值的MRI重建.
  • 实现一个双层层次的层次约束 (HC),以强制执行复杂值图像的稀疏表示.
  • 将HC集成到近位算法中,并使用交替的优化过程来最大限度地减少低采样工件.

主要成果:

  • 拟议的方法成功地同时重建复杂值的MRI图像的幅度和相位组分.
  • 实验结果表明,与现有的CS-MRI技术相比,性能优越.
  • 该方法有效地减少了k空间低样本引入的工件,特别是在相规律化重建中.

结论:

  • 开发的基于NSCT的层次约束方法为加速复杂值MRI重建提供了有效的方法.
  • 同时的大小和相位图像重建提高了诊断潜力,特别是神经退行性疾病.
  • 这种技术代表了MRI压缩传感的重大进步,提高了速度和诊断准确度.