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

Magnetic Resonance Imaging-Based Psoas Muscle Volume as an Additional Risk Factor for Fontan Failure: A Prospective Cohort Study.

Journal of the American Heart Association·2026
Same author

Transcranial direct current stimulation promotes functional recovery in rats with traumatic brain injury by inhibiting SLC7A11-mediated Disulfidptosis and Neuroinflammation.

Experimental neurology·2026
Same author

Dynamic volume perfusion CT for preoperative multidimensional resectability assessment of pancreatic ductal adenocarcinoma.

Frontiers in oncology·2026
Same author

Validation of the DSM-5 internet gaming disorder framework for clinical diagnosis of problematic social media usage.

Addictive behaviors reports·2026
Same author

Ferumoxytol-enhanced Ultrashort Echo Time MRI of Cardiovascular Stents in Patients with Congenital Heart Disease: A Feasibility Study.

Radiology. Cardiothoracic imaging·2026
Same author

Single-cell transcriptome analysis reveals mechanisms by which hippocampal deep brain stimulation promotes neurorepair and microglial subpopulation remodeling in ischemic stroke.

Journal of translational medicine·2026
Same journal

Self-supervised isotropic reconstruction for abnormality detection in anisotropic MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

WDBDM: Wavelet-based dual-branch diffusion model for low-dose CT and PET denoising.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

ScribSAM: A robust scribble-supervised framework for spatiotemporal segmentation of breast lesions in ultrasound videos.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

Anatomically and biochemically guided deep image prior for sodium MRI denoising.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

Segment Anything Model for medical image segmentation: A review.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
Same journal

HiCAF-Net: A Hierarchical Cross-Attention Fusion framework for cross-cancer subtype classification using histopathological and genomic data.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026
查看所有相关文章

相关实验视频

Updated: Jun 12, 2025

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

12.9K

用无监督生成模型在时间方向上进行动态MRI插值.

Corbin Maciel1, Qing Zou2

  • 1Department of Biomedical Engineering, University of Texas Southwestern Medical Center, Dallas, USA.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
|September 26, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了用于心脏电影MRI的新型无监督神经网络,增强了时间分辨率而不延长扫描时间. CINN框架有效地插入心脏影像图像,改善动态心脏功能评估.

关键词:
心脏影像核磁共振成像 (MRI)深度生成模型深度生成模型时间间的插值.没有监督的学习学习.

更多相关视频

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

11.6K
Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.3K

相关实验视频

Last Updated: Jun 12, 2025

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

12.9K
Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

11.6K
Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.3K

科学领域:

  • 医学成像医学成像
  • 医疗保健中的人工智能
  • 心血管诊断心血管诊断

背景情况:

  • 心脏影像核磁共振 (MRI) 对于评估心脏功能至关重要,但受到长时间的获取时间和喘息要求的限制.
  • 这些局限性阻碍了详细的动态分析和患者的舒适性.

研究的目的:

  • 开发一个无监督的神经网络框架,用于心脏影像MRI的时间插值.
  • 目标是增加时间分辨率,而不会延长获取时间.

主要方法:

  • 一个特定对象的无监督生成神经网络 (CINN) 设计用于时间插值.
  • 该网络从潜伏矢量中学习心脏相位,并生成电影图像,通过潜伏矢量操纵实现插值.
  • 使用SNR,SSIM,PSNR和Tenengrad清晰度等指标对最先进的方法和地面真相数据进行定量和定性评估.

主要成果:

  • 该CINN框架在学习生成任务和执行时间插值方面表现出了熟练.
  • 定量和定性比较证实了该框架在心脏膜插曲中的有效性.
  • 图像质量评估指标验证了插值的高质量输出.

结论:

  • 提出的生成模型成功地学习了心脏电影MRI的潜在生成任务.
  • 它有效地执行高质量的时间插值,为增强的心脏成像提供了一个有前途的解决方案.