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

Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

1.5K
Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
1.5K
Two-Dimensional (2D) NMR: Overview01:12

Two-Dimensional (2D) NMR: Overview

1.4K
The 1D NMR spectrum of large and complex molecules like natural products has complicated splitting patterns and overlapping signals, which can be easily interpreted using 2-dimensional (2D) NMR. Unlike 1D NMR, 2D NMR has two frequency axes that provide the coupling information between the nucleus A and nucleus B in a molecule. The process from which 2D spectra are obtained has four steps.
The first step is the preparation period, during which nucleus A is excited with a radiofrequency pulse....
1.4K
Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

8.9K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
8.9K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

223
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
223
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.6K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.6K

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

New Growth, New Opportunities.

Journal of medical imaging (Bellingham, Wash.)·2025
Same author

White matter hyperintensities and relapse risk in late-life depression.

Journal of affective disorders·2025
Same author

Unsupervised discovery of clinical disease signatures using probabilistic independence.

Journal of biomedical informatics·2025
Same author

Multi-contrast computed tomography atlas of healthy pancreas with dense displacement sampling registration.

Journal of medical imaging (Bellingham, Wash.)·2025
Same author

The effect of Alzheimer's disease genetic factors on limbic white matter microstructure.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging.

IS&T International Symposium on Electronic Imaging·2025
Same journal

Progressive axonal degeneration in white matter pathways traversing peritumoral penumbra in frontotemporal glioma.

Computational diffusion MRI. CDMRI (Workshop)·2026
Same journal

Introducing QuantConn: Overcoming challenging diffusion acquisitions with harmonization.

Computational diffusion MRI. CDMRI (Workshop)·2025
查看所有相关文章

相关实验视频

Updated: Jan 9, 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

26.9K

一个统一的学习模型,用于估计在异质多层扩散加权MRI上的纤维方向分布函数.

Tianyuan Yao1, Nancy Newlin1, Praitayini Kanakaraj1

  • 1Vanderbilt University, Nashville, TN 37215, USA.

Computational diffusion MRI. CDMRI (Workshop)
|December 1, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的单阶段深度学习网络,用于从扩散MRI数据中估计纤维方向分布函数 (fODF). 该方法有效地处理多序列,优于现有的多阶段方法.

关键词:
这是一个DW-MRI.多个shell 深度学习

更多相关视频

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
12:09

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

Published on: January 8, 2013

14.0K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

29.1K

相关实验视频

Last Updated: Jan 9, 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

26.9K
Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
12:09

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

Published on: January 8, 2013

14.0K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

29.1K

科学领域:

  • 神经成像是一种神经成像.
  • 生物医学工程 生物医学工程
  • 计算神经科学是一种神经科学.

背景情况:

  • 扩散权重MRI (DW-MRI) 测量生物组织中的水扩散,这对于理解微观结构至关重要.
  • 最近的进展侧重于辐射b值依赖,以改进组织分类和微型架构估计.
  • 现有的深度学习方法通常需要多阶段的策略,并依赖于中间表示.

研究的目的:

  • 开发一个统一的,单阶段的深度学习网络,用于高效的光纤导向分布函数 (fODF) 估计.
  • 为了从异质的多DW-MRI序列中实现准确的fODF估计.
  • 将拟议的单阶段方法与传统的多阶段方法的性能进行比较.

主要方法:

  • 开发了一种新的单阶段球形卷积神经网络.
  • 该网络使用人类连接组项目 (HCP) 年轻成年人测试复试扫描数据进行了培训和验证.
  • 使用异质的多,脱落和单DW-MRI序列来评估性能.

主要成果:

  • 拟议的单阶段网络证明了高效和准确的fODF估计.
  • 该方法的性能优于之前的多阶段深度学习方法.
  • 在各种DW-MRI序列类型中观察到强大的性能,包括单数据.

结论:

  • 开发的统一动态网络为DW-MRI中fODF估计提供了更有效和更有效的方法.
  • 这种单阶段方法简化了微结构成像的深度学习管道.
  • 这些发现表明,在神经科学中改善诊断和研究应用的潜力.