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

The effect of physical activity on brain structure and cognitive function in the population-based cohort of LIFE-Adult Study.

eLife·2026
Same author

Joint trajectories of brain atrophy, white matter hyperintensities and cognition quantify brain maintenance.

Nature communications·2026
Same author

Early Multimodal Motor Training After Stroke Promotes Motor Recovery and Whole-Brain Structural Remodeling.

Journal of the American Heart Association·2026
Same author

Quantification of amyotrophic lateral sclerosis (ALS) disease accumulation with T1-weighted high-resolution magnetic resonance imaging: validation in an independent cohort.

Journal of neurology·2026
Same author

Multiscale characterization of cortical signatures in positive and negative schizotypy: a worldwide ENIGMA study.

Molecular psychiatry·2026
Same author

Dysfunction of the episodic memory network in the Alzheimer's disease cascade.

Nature communications·2026

相关实验视频

Updated: Jan 10, 2026

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

9.4K

使用CAT12工具箱进行结构MRI的基于细分的质量控制.

Robert Dahnke1,2,3, Polona Kalc1,2, Gabriel Ziegler4

  • 1Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena 07747, Germany.

GigaScience
|November 29, 2025
PubMed
概括

这项研究引入了结构性MRI扫描的新质量评估工具. 它帮助研究人员和临床医生快速识别和解决图像工件,提高磁共振成像分析中的数据可靠性.

关键词:
这就是为什么MRI是MRI.大脑大脑大脑的大脑大脑运动文物 运动文物质量评估质量评估的质量评估.质量控制质量控制质量控制细分化 细分化的细分化

更多相关视频

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging
11:03

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

Published on: November 10, 2015

9.9K
Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

49.2K

相关实验视频

Last Updated: Jan 10, 2026

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

9.4K
High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging
11:03

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

Published on: November 10, 2015

9.9K
Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

49.2K

科学领域:

  • 神经成像是一种神经成像.
  • 医学图像分析 医学图像分析

背景情况:

  • 磁共振图像 (MRI) 的质量显著影响分析结果.
  • 扫描仪,协议和运动等工件的变化可能会导致结果偏差.
  • 可靠的图像质量评估对于识别异常值至关重要.

研究的目的:

  • 开发和验证结构性 (T1加权) MRI 的质量评估框架.
  • 标准化图像质量测量和创建一个综合的评级系统.
  • 为了促进异常值的识别,特别是那些具有运动工件的异常值.

主要方法:

  • 在SPM/CAT12软件中使用了组织分类.
  • 引入并将多个图像质量测量标准化为质量尺度.
  • 将措施组合成一个综合的结构图像质量评级.
  • 使用合成和真实数据集评估了强度.

主要成果:

  • 拟议的质量指标对模拟的细分问题和缩,年龄,性别,大脑大小和疾病的变化具有强大影响.
  • 该框架通过检测协议内偏差,有效地促进了运动工件的分离.
  • 综合评级系统有助于解释和快速识别异常值.

结论:

  • 开发的质量控制框架是一个简单而强大的工具.
  • 它适用于研究和临床环境中的应用.
  • 提高MRI数据分析的可靠性和有效性.