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

Computed Tomography01:10

Computed Tomography

7.6K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
7.6K
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

1.3K
Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
1.3K
Brain Imaging01:14

Brain Imaging

1.0K
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
1.0K
Parallel Processing01:20

Parallel Processing

950
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
950

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

GLP-1 receptor agonists for weight management and potential thromboembolic risk reduction in high risk population with cancer, diabetes, cardiovascular disease: A systematic review.

Disease-a-month : DM·2026
Same author

Approved weight loss drugs for obesity with a thorough emphasis on GLP-1 agonist medications: A systematic review.

Disease-a-month : DM·2026
Same author

Takotsubo cardiomyopathy: Advances in pathophysiology, diagnostic biomarkers, genetic insights, multisystemic involvement, treatment updates & multidisciplinary interventions.

Disease-a-month : DM·2025
Same author

The role and benefits of ketogenic diet in modulating inflammation in multiple sclerosis: A systematic review and meta-analysis.

Disease-a-month : DM·2025
Same author

Specific targeting of brain endothelial cells using enhancer AAV vectors.

Neuron·2025
Same author

The integration of artificial intelligence into clinical medicine: Trends, challenges, and future directions.

Disease-a-month : DM·2025
Same journal

Developmental trajectories of vocal behaviors in common marmosets as a reference framework for neurobehavioral studies.

Frontiers in neural circuits·2026
Same journal

Fleeing is believing: adaptive behavior under social threat as an inference process.

Frontiers in neural circuits·2026
Same journal

A modular and flexible pipeline for intraoperative electrode reconstruction and localization in patients with brain lesions.

Frontiers in neural circuits·2026
Same journal

Functional implications of atypical action potential generation in the (patho)physiological brain: from developmental program to glioma.

Frontiers in neural circuits·2026
Same journal

Loss of function of Noggin inhibits glial scar formation and motor function recovery after spinal cord injury.

Frontiers in neural circuits·2026
Same journal

Cross domain consistency of aesthetic preference-driven social behavior.

Frontiers in neural circuits·2026
查看所有相关文章

相关实验视频

Updated: May 1, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

26.2K

大脑图像数据处理使用Texera上的协作数据工作流程.

Yunyan Ding1, Yicong Huang1, Pan Gao2

  • 1Department of Computer Science, University of California, Irvine, Irvine, CA, United States.

Frontiers in neural circuits
|July 25, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一个新的管道,用于从小鼠大脑样本创建详细的3D大脑模型. 泰克斯拉平台促进了协作,并增强了大规模的神经电路数据处理和分析.

关键词:
3D可视化的3D可视化组织细胞 (TissueCyte) 是一种细胞.循环追踪 循环追踪 循环追踪 循环追踪数据分析数据分析.图像拼接 图像拼接 图像拼接鼠标的大脑 鼠标大脑

更多相关视频

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

12.3K
Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
10:23

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Published on: June 23, 2023

2.5K

相关实验视频

Last Updated: May 1, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

26.2K
A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

12.3K
Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
10:23

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Published on: June 23, 2023

2.5K

科学领域:

  • 神经科学是一个神经科学.
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 绘制三维 (3D) 神经电路对理解大脑功能至关重要.
  • 现有的3D脑图绘制方法可能很复杂,需要专门的专业知识.

研究的目的:

  • 介绍一条用于从小鼠大脑样本生成详细的3D大脑模型的新管道.
  • 为了利用Texera协作数据分析平台进行跨学科的神经科学研究.

主要方法:

  • 使用了来自连续二光子断层扫描/TissueCyte系统的图像.
  • 开发了一个管道,将图像拼接到脑部部分图像中,并构建3D全脑数据集.
  • 在Texera平台内采用专门的优化方法.

主要成果:

  • 成功地将小鼠大脑样本转化为详细的3D大脑模型.
  • 启用下游分析,如3D全脑注册,以天文图谱为基础的细分,细胞计数和体积可视化.
  • 在工作流程操作中取得了显著的性能提升.

结论:

  • 开发的管道和Texera平台为神经科学中基于图像的大规模数据处理提供了有效的方法.
  • 这种用户友好的平台促进了神经电路分析的跨学科合作.
  • 预计神经科学界将采用这种方法进行先进的大脑绘图研究.