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Related Concept Videos

Structural Joints: Synovial Joints01:16

Structural Joints: Synovial Joints

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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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Structural Joints: Fibrous Joints01:03

Structural Joints: Fibrous Joints

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Fibrous joints are a type of joint where the bones are connected by fibrous connective tissue. These joints provide stability and minimal to no movement between the articulating bones. There are three types of fibrous joints.
Suture
All the bones of the skull, except for the mandible, are joined to each other by a fibrous joint called a suture. The fibrous connective tissue found at a suture strongly unites the adjacent skull bones and thus helps to protect the brain and form the face. In...
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Structural Joints: Cartilaginous Joints01:17

Structural Joints: Cartilaginous Joints

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As the name indicates, at a cartilaginous joint, the adjacent bones are united by cartilage, a tough but flexible type of connective tissue. Unlike synovial joints, these types of joints lack a joint cavity and involve bones joined together by either hyaline cartilage or fibrocartilage.
There are two types of cartilaginous joints:
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A synchondrosis ("joined by cartilage") is a cartilaginous joint where bones are connected by hyaline cartilage. Synchondrosis may be temporary...
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Joints01:26

Joints

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Joints, also called articulations or articular surfaces, are points at which ligaments or other tissues connect adjacent bones. Joints permit movement and stability, and can be classified based on their structure or function.
Structural joint classifications are based on the material that makes up the joint as well as whether or not the joint contains a space between the bones. Joints are structurally classified as fibrous, cartilaginous, or synovial.
Fibrous Joints Are Immovable
The bones of a...
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Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
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Method of Joints01:30

Method of Joints

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The method of joints is a commonly used technique to analyze the forces in structural trusses. The method is based on the principle of equilibrium, which assumes that the truss members are connected by frictionless pins. The forces at each joint can be determined by considering the equilibrium of the forces acting on that joint.
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Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
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Scalable Joint Segmentation and Registration Framework for Infant Brain Images.

Pei Dong1, Li Wang1, Weili Lin1

  • 1Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA.

Neurocomputing
|February 9, 2018
PubMed
Summary

This study introduces a novel joint segmentation and registration method for infant brain MRI. The technique enhances accuracy in early brain development studies by enabling images to assist each other.

Keywords:
Joint segmentation and registrationand infant brain MR imageslongitudinal growth trajectorymulti-atlas patch based label fusion

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Area of Science:

  • Medical Imaging
  • Neuroscience
  • Developmental Biology

Background:

  • The first year of life is critical for infant brain development.
  • Accurate measurement of structural changes in infant brains relies on image segmentation and registration.
  • Independent infant image segmentation or registration faces challenges due to rapid developmental changes.

Purpose of the Study:

  • To develop a joint segmentation and registration framework for infant brain MRI.
  • To overcome challenges in infant image analysis caused by dynamic appearance changes.
  • To improve the accuracy of early brain development studies.

Main Methods:

  • A one-year-old infant image is used as a reference.
  • Tissue probability maps are estimated using sparse patch-based multi-atlas label fusion.
  • Probability maps initialize level set segmentation, guiding registration.
  • Learned growth trajectories enhance segmentation by propagating reference domain heuristics.

Main Results:

  • Established correspondences between infant images despite appearance changes.
  • Enhanced segmentation accuracy through mutual assistance between segmentation and registration.
  • Demonstrated scalability for registering infant images with significant age gaps.
  • Achieved promising results for infant brain MR images from 2 weeks to 1 year old.

Conclusions:

  • The proposed joint method effectively assists image segmentation and registration.
  • This framework is scalable and applicable to various early brain development studies.
  • The method shows significant applicability in analyzing infant brain MR images.