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

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

Deep-learning denoising for ultrahigh-resolution photon-counting detector CT: phantom and in vivo evaluation of non-calcified coronary plaques.

The international journal of cardiovascular imaging·2026
Same author

Impact of Deep Learning-Based Denoising on Image Quality and Diagnostic Confidence in Neurovascular Ultrahigh-Resolution Photon-Counting CT Angiography.

AJNR. American journal of neuroradiology·2026
Same author

Added value of photon-counting CT for triple rule-out imaging: A propensity-matched comparison with energy-integrating CT.

Journal of cardiovascular computed tomography·2026
Same author

Field strength dependence, physiologic correlates, and prognostic significance of ventricular blood pool T2 mapping on cardiovascular magnetic resonance imaging.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance·2026
Same author

Cardiac magnetic resonance-derived left atrioventricular coupling index predicts outcome in reduced ejection fraction.

ESC heart failure·2026
Same author

Photon-counting CT in cardiac imaging: multi-institutional guidance on technical principles, clinical evidence, and practical protocols.

European journal of radiology·2026

相关实验视频

Updated: Jul 10, 2025

Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation
07:50

Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation

Published on: January 27, 2023

2.1K

特性跟踪应变参数在高度加速和传统采集之间有所不同:一个多软件评估

Moritz C Halfmann1,2, Tim Klimzak1, U Joseph Schoepf3

  • 1Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University.

Journal of thoracic imaging
|November 20, 2023
PubMed
概括
此摘要是机器生成的。

心脏MRI后处理软件显示压缩传感 (CS) 和传统电影序列之间有很强的一致性,但CS采集中的较低应变和体积参数需要意识到患者的准确后续.

更多相关视频

Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens
09:29

Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens

Published on: January 24, 2016

9.5K
Intermediate Strain Rate Material Characterization with Digital Image Correlation
07:59

Intermediate Strain Rate Material Characterization with Digital Image Correlation

Published on: March 1, 2019

7.2K

相关实验视频

Last Updated: Jul 10, 2025

Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation
07:50

Measuring Local Tissue Strains in Tendons via Open-Source Digital Image Correlation

Published on: January 27, 2023

2.1K
Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens
09:29

Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens

Published on: January 24, 2016

9.5K
Intermediate Strain Rate Material Characterization with Digital Image Correlation
07:59

Intermediate Strain Rate Material Characterization with Digital Image Correlation

Published on: March 1, 2019

7.2K

科学领域:

  • 心血管成像 - 心血管成像
  • 医学物理 医学物理
  • 放射学 放射学是一门学科.

背景情况:

  • 加速心脏MRI协议,包括压缩传感 (CS),使得更快,更有效的收购.
  • 评估CS和传统电影序列的后处理软件对于临床应用至关重要.

研究的目的:

  • 评估心脏MRI后处理中的软件间和交互采集变异性.
  • 为了比较软件解决方案在压缩传感 (CS) 和传统电影序列上的性能.

主要方法:

  • 106名参与者 (志愿者和心肌病患者) 接受了3T心脏MRI,使用传统的cine和CS序列.
  • 后处理是使用三个不同的软件解决方案进行的.
  • 使用布兰德-阿尔特曼分析和类内相关系数来评估一致性;使用克鲁斯卡尔-瓦利斯测试来分析差异.

主要成果:

  • 对于大多数参数,发现了显著的软件间和交互收购差异.
  • 收购之间的类内相关系数强到优异 (≥0.81).
  • 布兰德-阿尔特曼分析显示,与CS数据相比,cine获取的偏差较小,传统的切断值在应用于CS数据时不会错误分类患者.

结论:

  • 具有追溯性封闭的CS收购产生的应变和体积参数比传统电影更低.
  • 尽管存在差异,但软件和收购类型之间存在很强的共识.
  • 对收购类型的认识对于后续工作至关重要,以防止由于不同的截止值而导致的错误分类.