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

Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

135
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,...
135

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

Dual-Stage Clean-Sample Selection for Incremental Noisy Label Learning.

Bioengineering (Basel, Switzerland)·2025
Same author

Segmentation of Portal Vein in Multiphase CTA Image Based on Unsupervised Domain Transfer and Pseudo Label.

Diagnostics (Basel, Switzerland)·2023
Same author

Prediction Model of Hemorrhage Transformation in Patient with Acute Ischemic Stroke Based on Multiparametric MRI Radiomics and Machine Learning.

Brain sciences·2022
Same author

Fusion of multimodality image and point cloud for spatial surface registration for knee arthroplasty.

The international journal of medical robotics + computer assisted surgery : MRCAS·2022
Same author

Prolactin related symptoms during risperidone maintenance treatment: results from a prospective, multicenter study of schizophrenia.

BMC psychiatry·2016
Same author

Methylation of Notch3 modulates chemoresistance via P-glycoprotein.

European journal of pharmacology·2016
Same journal

Correction: Komatsu et al. Three-Dimensional Visualization and Detection of the Pulmonary Venous-Left Atrium Connection Using Artificial Intelligence in Fetal Cardiac Ultrasound Screening. <i>Bioengineering</i> 2026, <i>13</i>, 100.

Bioengineering (Basel, Switzerland)·2026
Same journal

Comparison of CO<sub>2</sub> Laser and Microdebrider in the Surgical Treatment of Pediatric Recurrent Respiratory Papillomatosis: A Retrospective Analysis.

Bioengineering (Basel, Switzerland)·2026
Same journal

Toward More Translational Tumor Models: Breast dECM-Based 3D Systems Capture Native Microenvironmental Cues.

Bioengineering (Basel, Switzerland)·2026
Same journal

Postural Stability Changes During the 4 Phases of the Half Squat: Kinematics Profile of the Center of Pressure and Center of Mass in High-Performance Weightlifters-A Pilot Study.

Bioengineering (Basel, Switzerland)·2026
Same journal

Definite Implant Position as Novel Readout for Effectiveness of Ridge Preservation Indicates to Beneficial Effect of Combined Treatment with Platelet-Rich Fibrin (PRF) and Xenogenic Biomaterial in Bone Regeneration.

Bioengineering (Basel, Switzerland)·2026
Same journal

Trueness and Precision of Intraoral Scanners for 3D-Printed Orthodontic Models with Attachments: An In Vitro Comparative Study.

Bioengineering (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Sep 10, 2025

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
10:39

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

2.4K

多标签条件扩散用于心脏MR图像增大和细分

Jianyang Li1,2,3, Xin Ma1, Yonghong Shi2,3

  • 1Academy of Engineering & Technology, Fudan University, Shanghai 200433, China.

Bioengineering (Basel, Switzerland)
|August 28, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了心脏MRI数据增强的新生成模型,提高了心脏病的细分精度. 这种方法可以增强数据集,从而获得更好的诊断见解和治疗规划.

关键词:
心脏MRI细分条件引导的扩散模型数据增强

更多相关视频

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
06:48

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

9.0K
Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

676

相关实验视频

Last Updated: Sep 10, 2025

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
10:39

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

Published on: May 24, 2022

2.4K
Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
06:48

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

9.0K
Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

676

科学领域:

  • 医学成像
  • 人工智能
  • 生物医学工程

背景情况:

  • 准确的心脏MRI细分对于诊断心脏病和计划治疗至关重要.
  • 高细分精度需要大量的注释数据集,这些数据集很难且很昂贵.
  • 深度学习模型的细分在很大程度上取决于培训数据的数量和质量.

研究的目的:

  • 使用条件导向的扩散生成模型开发心脏MRI的新数据增强框架.
  • 应对有限的心脏MRI数据集的挑战.
  • 通过增强数据集来提高心脏细分任务的性能.

主要方法:

  • 提出了一个两阶段的生成数据增强框架.
  • 第一个阶段:标签扩散模块根据解剖学先验生成了现实的多类空间面具.
  • 第二阶段:使用空间适应性正常化 (SPADE) 模块在这些面具上生成心脏MRI图像以获得结构准确性.

主要成果:

  • 生成增强框架显著增加了数据集样本数量.
  • 与传统方法相比,心脏细分的准确性提高了5%至10%.
  • 在生成图像的质量和增强效果之间观察到强烈的相关性.

结论:

  • 拟议的框架为心脏图像分析的数据短缺提供了强有力的解决方案.
  • 使用条件导向扩散模型的生成数据增强可以大大提高下游细分任务.
  • 这种方法对心脏病诊断和治疗的临床应用有直接的好处.