Jove
Visualize
联系我们

相关概念视频

Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...

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

K-CC-MoCo: A Fast k-Space-Based Respiratory Motion Correction for Highly Accelerated First-Pass Perfusion Cardiovascular MR.

Magnetic resonance in medicine·2026
Same author

Versatile and Highly Efficient MRI Simulation of Arbitrary Motion in KomaMRI.

Magnetic resonance in medicine·2025
Same author

Sampling of non-Gaussian Ensemble Average Propagators for the simulation of diffusion magnetic resonance images.

Magnetic resonance in medicine·2025
Same author

Brain tumor enhancement prediction from pre-contrast conventional weighted images using synthetic multiparametric mapping and generative artificial intelligence.

Quantitative imaging in medicine and surgery·2025
Same author

KomaMRI.jl: An open-source framework for general MRI simulations with GPU acceleration.

Magnetic resonance in medicine·2023
Same author

Diffusion sampling schemes: A generalized methodology with nongeometric criteria.

Magnetic resonance in medicine·2023
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

相关实验视频

Updated: Jun 9, 2026

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging
11:13

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Published on: May 24, 2021

6.4K

多设备并行MRI重建:低采样5D心脏CINE的高效分区

Emilio López-Ales1, Rosa-María Menchón-Lara1, Federico Simmross-Wattenberg1

  • 1Laboratorio de Procesado de Imagen, Universidad de Valladolid, Campus Miguel Delibes sn., 47011 Valladolid, Spain.

Sensors (Basel, Switzerland)
|February 24, 2024
PubMed
概括

这项研究引入了多图形处理单元 (GPU) 系统,以加速心脏MRI重建. 该方法有效处理大型数据集,提高诊断成像的速度和心脏状况评估的有效性.

关键词:
核磁共振成像 (MRI) 重建的重建心脏 CINE 的情况.压缩感应传感器 压缩感应多个GPU多个GPU多个设备的多个设备.平行计算是平行计算中的一个.

更多相关视频

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

498
Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

278

相关实验视频

Last Updated: Jun 9, 2026

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging
11:13

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Published on: May 24, 2021

6.4K
Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

498
Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

278

科学领域:

  • 医疗成像医学成像
  • 计算科学 计算科学
  • 心血管诊断心血管诊断服务

背景情况:

  • 心脏影像核磁共振 (MRI) 对于诊断心脏病至关重要,但高分辨率成像产生大量数据集.
  • 处理这些大型数据集带来了计算挑战,可能会减缓诊断成像效率.
  • 现有的单个GPU系统在处理高分辨率,五维心脏MRI数据时面临内存限制.

研究的目的:

  • 开发和评估用于加速心脏MRI重建的多GPU系统.
  • 为了克服单个GPU内存的局限性,用于处理大型,高分辨率的心脏MRI数据集.
  • 提高心脏MRI图像重建的效率和速度,以提高诊断能力.

主要方法:

  • 使用多图形处理单元 (GPU) 系统并行处理心脏MRI数据.
  • 实现了数据分区,以管理跨多个GPU的大数据集,克服单个设备内存限制.
  • 采用OpenCL技术实现跨平台兼容性和系统适应性.

主要成果:

  • 多GPU系统显著加速了高分辨率,五维心脏MRI的重建过程.
  • 该方法成功处理了大量的数据,同时保持了图像完整性.
  • 与单个设备的限制相比,在生成心脏MRI图像方面表现出更高的效率.

结论:

  • 拟议的多设备GPU方法有效地解决了心脏MRI中的计算挑战.
  • 这一进步加速了图像重建,促进了更快,更有效的心脏健康评估.
  • 该系统为现代医学成像需求提供了一个可扩展和适应的解决方案.