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相关概念视频

Functional Classification of Joints01:09

Functional Classification of Joints

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Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
4.1K
Structural Classification of Joints01:20

Structural Classification of Joints

3.4K
Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
3.4K

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相关实验视频

Updated: Jun 29, 2025

Author Spotlight: Advancing 3D Cytoarchitecture Analysis - Rapid Volumetric Reconstruction of the Human Brain
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Author Spotlight: Advancing 3D Cytoarchitecture Analysis - Rapid Volumetric Reconstruction of the Human Brain

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用于高分辨率fMRI关节重建和动态定量化的多重调节器.

Shouchang Guo, Jeffrey A Fessler, Douglas C Noll

    IEEE transactions on medical imaging
    |March 25, 2024
    PubMed
    概括

    振荡稳态成像 (OSSI) 在fMRI中提供更高的SNR. 一个新的基于物理学的模型 (OSSIMM) 可以更快地重建高分辨率的fMRI图像,而无需光滑,从而改善时间分辨率.

    科学领域:

    • 磁共振成像技术 磁共振成像技术
    • 功能磁共振成像 (fMRI) 是一种功能性磁共振成像技术.
    • 图像重建 图像的重建

    背景情况:

    • 振荡稳态成像 (OSSI) 与标准fMRI相比,提供了优越的信号噪声比率 (SNR).
    • 由于OSSI的非线性振荡模式,需要获得多个图像,从而影响时间分辨率.
    • 现有的子空间模型对于OSSI数据的独特信号特征是不理想的.

    研究的目的:

    • 开发一种用于重建OSSI fMRI图像的先进方法.
    • 改善OSSI收购的时间解决方案.
    • 为了实现OSSI fMRI数据的联合重建和动态量化.

    主要方法:

    • 开发了一种基于物理的多元模型 (OSSIMM) 用于OSSI信号生成.
    • 集成的MR物理作为一个调节器,用于低样本的OSSI重建.
    • 利用OSSIMM进行联合重建和量化,绕过子空间模型.

    主要成果:

    • 在图像重建中,OSSIMM实现了12倍的加速度因子.
    • 重建了高分辨率的fMRI图像,没有空间或时间光滑.
    • 启用了参数的动态量化,如R2*地图,时间分辨率为150毫秒.

    更多相关视频

    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
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    Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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    Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

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    相关实验视频

    Last Updated: Jun 29, 2025

    Author Spotlight: Advancing 3D Cytoarchitecture Analysis - Rapid Volumetric Reconstruction of the Human Brain
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    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
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    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

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    Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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    Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

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    结论:

    • OSSIMM有效地模拟了OSSI信号的非线性,将收购的缺点转化为优势.
    • 拟议的方法显著提高了OSSI fMRI的时间分辨率和重建质量.
    • OSSIMM促进了快速,高准确度的fMRI采集和动态参数映射.