Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Functional Classification of Joints01:09

Functional Classification of Joints

4.1K
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

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A vendor-neutral functional MRI acquisition protocol for multi-site studies.

Aperture neuro·2026
Same author

Phantom- and simulation-based validation of combined diffusion relaxometry in ex vivo ADRD white matter.

bioRxiv : the preprint server for biology·2026
Same author

Smooth optimization using global and local low-rank regularizers.

SIAM journal on imaging sciences·2026
Same author

Bilevel Optimized Implicit Neural Representation for Scan-Specific Accelerated MRI Reconstruction.

IEEE transactions on medical imaging·2026
Same author

Scan-Adaptive MRI Undersampling Using Neighbor-based Optimization (SUNO).

IEEE transactions on computational imaging·2026
Same author

Spatiotemporal Maps for Dynamic MRI Reconstruction.

IEEE transactions on computational imaging·2026

Related Experiment Video

Updated: Jun 29, 2025

Author Spotlight: Advancing 3D Cytoarchitecture Analysis - Rapid Volumetric Reconstruction of the Human Brain
06:52

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

Published on: January 26, 2024

2.0K

Manifold Regularizer for High-Resolution fMRI Joint Reconstruction and Dynamic Quantification.

Shouchang Guo, Jeffrey A Fessler, Douglas C Noll

    IEEE Transactions on Medical Imaging
    |March 25, 2024
    PubMed
    Summary
    This summary is machine-generated.

    Oscillating Steady-State Imaging (OSSI) offers higher SNR in fMRI. A new physics-based model (OSSIMM) reconstructs high-resolution fMRI images faster without smoothing, improving temporal resolution.

    More Related Videos

    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
    09:30

    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

    Published on: December 18, 2016

    19.5K
    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

    28.4K

    Related Experiment Videos

    Last Updated: Jun 29, 2025

    Author Spotlight: Advancing 3D Cytoarchitecture Analysis - Rapid Volumetric Reconstruction of the Human Brain
    06:52

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

    Published on: January 26, 2024

    2.0K
    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
    09:30

    Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

    Published on: December 18, 2016

    19.5K
    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

    28.4K

    Area of Science:

    • Magnetic Resonance Imaging
    • Functional Magnetic Resonance Imaging (fMRI)
    • Image Reconstruction

    Background:

    • Oscillating Steady-State Imaging (OSSI) provides superior Signal-to-Noise Ratio (SNR) compared to standard fMRI.
    • OSSI's nonlinear oscillation pattern necessitates acquiring multiple images, impacting temporal resolution.
    • Existing subspace models are suboptimal for OSSI data's unique signal characteristics.

    Purpose of the Study:

    • To develop an advanced method for reconstructing OSSI fMRI images.
    • To improve temporal resolution in OSSI acquisitions.
    • To enable joint reconstruction and dynamic quantification of OSSI fMRI data.

    Main Methods:

    • Developed a physics-based manifold model (OSSIMM) for OSSI signal generation.
    • Integrated MR physics as a regularizer for undersampled OSSI reconstruction.
    • Utilized OSSIMM for joint reconstruction and quantification, bypassing subspace models.

    Main Results:

    • OSSIMM achieved a 12x acceleration factor in image reconstruction.
    • Reconstructed high-resolution fMRI images without spatial or temporal smoothing.
    • Enabled dynamic quantification of parameters like R2* maps with 150 ms temporal resolution.

    Conclusions:

    • OSSIMM effectively models OSSI signal nonlinearity, turning acquisition disadvantages into advantages.
    • The proposed method significantly enhances temporal resolution and reconstruction quality for OSSI fMRI.
    • OSSIMM facilitates rapid, high-fidelity fMRI acquisition and dynamic parameter mapping.