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Related Concept Videos

Functional Classification of Joints01:09

Functional Classification of Joints

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 immobile...
Structural Classification of Joints01:20

Structural Classification of Joints

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...
Development of the Limb Synovial Joints01:07

Development of the Limb Synovial Joints

Joints form during embryonic development in conjunction with the formation and growth of the associated bones. The embryonic tissue that gives rise to all bones, cartilage, and connective tissues of the body is called mesenchyme.
The mesenchymal stem cells differentiate into chondrocytes that form the hyaline cartilage, and later the cartilaginous model of the bone. This model further transforms into a bone. This process is known as endochondral ossification.
During development, the limbs...
Ankle Joint01:10

Ankle Joint

The ankle is formed by the talocrural joint (crural = leg). It consists of the articulations between the talus bone of the foot and the distal ends of the tibia and fibula of the leg. The superior aspect of the talus bone is square-shaped and has three areas of articulation. The top of the talus articulates with the inferior tibia. This is the portion of the ankle joint that carries the body weight between the leg and foot. The sides of the talus are firmly held in position by the articulations...
Classification of Bones01:18

Classification of Bones

The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The long...
Structural Joints: Synovial Joints01:16

Structural Joints: Synovial Joints

Synovial joints are the most common type of joint in the body. A key structural characteristic for a synovial joint is the presence of a joint cavity. This fluid-filled space is where the articulating surfaces of the bones contact each other. Also, unlike fibrous or cartilaginous joints, the articulating bone surfaces at a synovial joint are not directly connected to each other with fibrous connective tissue or cartilage. This gives the bones of a synovial joint the ability to move smoothly...

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Related Experiment Video

Updated: Jun 30, 2026

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
09:32

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

Published on: April 11, 2018

Artificial Intelligence Models for Classifying Wrist Ligament Injuries Using Synthetically-Generated Joint Proximity

Hsuan-Yu Chen, Jon Camp, Taylor P Trentadue

    Biorxiv : the Preprint Server for Biology
    |June 29, 2026
    PubMed
    Summary
    This summary is machine-generated.

    Artificial intelligence (AI) models trained on synthetic data from finite element models (FEMs) show promise for diagnosing wrist ligament injuries. This approach uses interosseous proximity maps to improve noninvasive diagnostic accuracy.

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    Treatment of Ligament Constructs with Exercise-conditioned Serum: A Translational Tissue Engineering Model
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    Treatment of Ligament Constructs with Exercise-conditioned Serum: A Translational Tissue Engineering Model

    Published on: June 11, 2017

    Related Experiment Videos

    Last Updated: Jun 30, 2026

    Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
    09:32

    Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

    Published on: April 11, 2018

    Treatment of Ligament Constructs with Exercise-conditioned Serum: A Translational Tissue Engineering Model
    08:03

    Treatment of Ligament Constructs with Exercise-conditioned Serum: A Translational Tissue Engineering Model

    Published on: June 11, 2017

    Area of Science:

    • Biomedical Engineering
    • Medical Imaging
    • Artificial Intelligence

    Background:

    • Diagnosing wrist ligament injuries is complex, necessitating early detection to prevent osteoarthritis.
    • Interosseous proximity maps from volumetric imaging offer insights into wrist joint health.
    • Artificial intelligence (AI) can potentially improve noninvasive diagnosis using imaging metrics.

    Purpose of the Study:

    • To demonstrate the feasibility of training AI models using synthetic data.
    • To generate synthetic interosseous proximity map data from finite element models (FEMs).
    • To develop AI models for classifying wrist ligament injuries.

    Main Methods:

    • Personalized wrist FEMs were created from 4D CT data.
    • 7,500 injury scenarios generated 9 million synthetic RGB images of proximity vector fields.
    • Mixed-input convolutional neural networks (CNNs) were developed and evaluated.

    Main Results:

    • CNNs achieved an average AUROC of 0.757 across all injury types.
    • Performance improved to an average AUROC of 0.824 for clinically relevant angles.
    • High sensitivities and specificities (>0.99) were observed in specific simulations.

    Conclusions:

    • Synthetic FEM data can effectively train AI for wrist ligament injury classification.
    • Proximity-based RGB images show potential as biomarkers for ligamentous injury.