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

Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.4K
Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
2.4K

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

IRF8 and IRF3 cooperatively regulate rapid interferon-β induction in human blood monocytes.

Blood·2011
Same author

Reduced order modeling of passive and quasi-active dendrites for nervous system simulation.

Journal of computational neuroscience·2011
Same author

Controlled synthesis and self-assembly of highly monodisperse Ag and Ag(2)S nanocrystals.

Chemistry (Weinheim an der Bergstrasse, Germany)·2011
Same author

Comparison of inlet geometry in microfluidic cell affinity chromatography.

Analytical chemistry·2011
Same author

Ion-exchange synthesis of a micro/mesoporous Zn2GeO4 photocatalyst at room temperature for photoreduction of CO2.

Chemical communications (Cambridge, England)·2011
Same author

A microarray-based approach identifies ADP ribosylation factor-like protein 2 as a target of microRNA-16.

The Journal of biological chemistry·2011

相关实验视频

Updated: Jun 10, 2025

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
10:59

Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands

Published on: July 26, 2014

14.4K

通过结构保存图形嵌入框架改进了MRF重建.

Peng Li, Yuping Ji, Yue Hu

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |October 16, 2024
    PubMed
    概括
    此摘要是机器生成的。

    这项研究引入了一种用于磁共振指纹 (MRF) 重建的新型图形嵌入框架. 它有效地减少了别名化文物和计算复杂性,提高了定量成像准确性.

    更多相关视频

    Topographical Estimation of Visual Population Receptive Fields by fMRI
    06:02

    Topographical Estimation of Visual Population Receptive Fields by fMRI

    Published on: February 3, 2015

    9.2K
    A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
    12:49

    A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

    Published on: September 28, 2019

    12.7K

    相关实验视频

    Last Updated: Jun 10, 2025

    Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
    10:59

    Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands

    Published on: July 26, 2014

    14.4K
    Topographical Estimation of Visual Population Receptive Fields by fMRI
    06:02

    Topographical Estimation of Visual Population Receptive Fields by fMRI

    Published on: February 3, 2015

    9.2K
    A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
    12:49

    A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

    Published on: September 28, 2019

    12.7K

    科学领域:

    • 医疗成像医学成像
    • 计算物理 计算物理
    • 数据科学数据科学数据科学

    背景情况:

    • 低采样磁共振指纹 (MRF) 方案导致别名文物,降低定量成像准确性.
    • 当前的重建方法往往无法利用MRF数据结构,并且具有很高的计算复杂性.
    • 像素智能数据先验与非局部和非线性相关性作斗争.

    研究的目的:

    • 开发一种新的MRF重建框架,利用MRF数据中的非线性和非局部冗余.
    • 通过减少计算复杂性和提高重建质量来解决现有方法的局限性.
    • 为了提高MRF成像的定量准确性.

    主要方法:

    • 提出了一个图形嵌入框架,将MRF数据和参数地图重建为图形节点.
    • 重建问题被重新定义为结构保存的图形嵌入问题.
    • 引入了一个用于估计图形结构的新方案,揭示了MRF数据节点的低维表示.

    主要成果:

    • 该框架保留了MRF数据和参数节点之间的内在图形结构,利用全局图形属性.
    • MRF数据恢复和参数图估计被集成到一个单一的优化问题中.
    • 计算复杂性的显著降低得到了实现,相对于数据采集长度的最小增加.

    结论:

    • 拟议的图形嵌入方法可以实现高质量的MRF数据和参数地图重建.
    • 与现有技术相比,该方法显著减少了计算时间.
    • 这一框架为准确和高效的定量MRF成像提供了一个有前途的解决方案.