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Related Concept Videos

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...
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Knee Joint01:23

Knee Joint

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The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
A total of seven ligaments support the knee joint. The patellar ligament, which is also attached to the quadriceps femoris...
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Classification of Bones01:18

Classification of Bones

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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...
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Structural Classification of Joints01:20

Structural Classification of Joints

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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...
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Bones of the Lower Limb: Femur and Patella01:16

Bones of the Lower Limb: Femur and Patella

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The femur is the body's longest and strongest bone spanning the thigh region. Its head articulates with the acetabulum of the hip bone to form the hip joint. A minor indentation on the medial side of the femoral head, called the fovea capitis, serves as the site of attachment for the ligament of the head of the femur. This weak ligament spans the femur and acetabulum and supports the hip joint. The narrowed region below the head is the neck of the femur. The inclination angle between the...
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Related Experiment Video

Updated: Apr 14, 2026

Automated Joint Space Detection Improves Bone Segmentation Accuracy
06:45

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

290

Surgically Relevant Knee Phenotypes: The Modified Coronal Plane Alignment of the Knee System-A Deep Learning-Based

Carmelo Burgio1, Karlos Zepeda1, Theofilos Karasavvidis1

  • 1Department of Orthopaedic Surgery, Adult Reconstruction and Joint Replacement Service, Hospital for Special Surgery, New York, New York.

The Journal of Arthroplasty
|April 12, 2026
PubMed
Summary
This summary is machine-generated.

A modified coronal plane alignment of the knee (CPAK) classification system, utilizing deep learning, accurately categorizes knee phenotypes. This objective approach aids surgical decision-making for various knee alignments.

Keywords:
classificationknee phenotypesnative alignmentpersonalized arthroplastytotal knee replacement

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Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
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Area of Science:

  • Orthopedics
  • Biomedical Engineering
  • Radiology

Background:

  • The Coronal Plane Alignment of the Knee (CPAK) classification system, comprising nine phenotypes, faces challenges in definition consistency and surgical application clarity.
  • A simplified, modified CPAK system is proposed to enhance accuracy and streamline surgical decision-making.

Purpose of the Study:

  • To automate knee phenotyping using a deep learning (DL) model.
  • To analyze the distribution of modified CPAK phenotypes in a large patient cohort.

Main Methods:

  • A deep learning model was employed to analyze full-limb radiographs from 972 patients (1,944 knees).
  • Measurements of the lateral distal femoral angle (LDFA) and medial proximal tibial angle (MPTA) were performed.
  • Knee phenotypes were classified based on overall limb alignment (aHKA) and joint-line angles (LDFA, MPTA).

Main Results:

  • Seven distinct phenotypes were identified, with five accounting for 99.2% of knees.
  • The most common phenotypes included varus knees (26.9%), neutral knees (25.6%), and valgus knees (24.2%).
  • Varus phenotypes were primarily tibial-driven (99.2%), while valgus phenotypes were femoral-driven (98.9%).

Conclusions:

  • The modified CPAK system offers an objective and practical evaluation of knee alignment.
  • This system provides a clear, surgically relevant assessment of coronal knee alignment by considering limb alignment and joint-line deformities.