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

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...
Internal Loadings in Structural Members: Problem Solving01:28

Internal Loadings in Structural Members: Problem Solving

When designing or analyzing a structural member, it is important to consider the internal loadings developed within the member. These internal loadings include normal force, shear force, and bending moment. Engineers can ensure that the structural member can support the applied external forces by calculating these internal loadings.
To illustrate this, let's consider a beam OC of 5 kN, inclined at an angle of 53.13° with the horizontal and supported at both ends. Determine the internal loadings...
Deformation of Member under Multiple Loadings01:11

Deformation of Member under Multiple Loadings

When a rod is made of different materials or has various cross-sections, it must be divided into parts that meet the necessary conditions for determining the deformation. These parts are each characterized by their internal force, cross-sectional area, length, and modulus of elasticity. These parameters are then used to compute the deformation of the entire rod.
In the case of a member with a variable cross-section, the strain is not constant but depends on the position. The deformation of an...
Bending of Members Made of Several Materials01:11

Bending of Members Made of Several Materials

In analyzing a structural member composed of two different materials with identical cross-sectional areas, it is crucial to understand how their distinct elastic properties affect the member's response under load. The analysis involves assessing stress and strain distributions using the transformed section concept, which accounts for variations in material properties.
Hooke's Law determines stress in each material, stating that stress is proportional to strain but varies due to each material's...
Types of Building Separation Joints01:23

Types of Building Separation Joints

Building separation joints divide large or complex building structures into smaller, discrete units that can move independently. These joints are categorized into three types: volume-change joints, settlement joints, and seismic separation joints.
Volume-change joints address the effects of expansion and contraction due to temperature and moisture variations. They are strategically placed at discontinuities in a building's mass where cracking is most likely and are spaced about 150 to 200 feet...
Design Example: Dimensioning of Concrete Masonry Construction01:13

Design Example: Dimensioning of Concrete Masonry Construction

For the construction of a storeroom using concrete masonry units, it's essential to align the dimensions of the structure with the actual sizes of the blocks and the intended mortar joints. On the site in question, there's a stockpile of concrete masonry blocks with a nominal size of eight by eight by sixteen inches, which are to be used in the construction of the storeroom.
The site engineer has laid out a plan for the storeroom with external dimensions of twelve feet in length and eight feet...

You might also read

Related Articles

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

Sort by
Same author

NExplore: Exploration with Neural Fields for Autonomous Scene Reconstruction.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Toward Semantically-Consistent Deformable 2D-3D Registration for 3D Craniofacial Structure Estimation From a Single-View Lateral Cephalometric Radiograph.

IEEE transactions on medical imaging·2024
Same author

Bi-Graph Reasoning for Masticatory Muscle Segmentation From Cone-Beam Computed Tomography.

IEEE transactions on medical imaging·2023
Same author

MOUNT: Learning 6DoF Motion Prediction Based on Uncertainty Estimation for Delayed AR Rendering.

IEEE transactions on visualization and computer graphics·2023
Same author

Dense correspondence of deformable volumetric images via deep spectral embedding and descriptor learning.

Medical image analysis·2022
Same author

Automated assessment of mandibular shape asymmetry in 3-dimensions.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics·2022

Related Experiment Video

Updated: Jun 7, 2026

A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth
10:50

A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth

Published on: April 8, 2020

9.6K

Adaptable cascaded registration for personalized maxilla completion and cleft defect volume estimation.

Yungeng Zhang1,2, Yuru Pei1, Yixiao Guo1

  • 1Key Laboratory of Machine Perception (MOE), Department of Machine Intelligence, School of Intelligence Science and Technology, Peking University, Beijing, China.

Medical Physics
|March 31, 2024
PubMed
Summary

This study introduces a novel deep registration framework to automatically complete maxilla defects in cleft lip and palate (CLP) patients using cone-beam computed tomography (CBCT) scans. The method accurately predicts cleft defect volumes, reducing manual annotation efforts.

Keywords:
adaptable cascaded registrationcleft defect volume estimationmaxilla completion

More Related Videos

Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment
07:32

Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment

Published on: February 23, 2024

1.1K
Author Spotlight: Development of a Novel Finite Element Analysis Model for Improved Orthognathic Surgical Techniques
07:16

Author Spotlight: Development of a Novel Finite Element Analysis Model for Improved Orthognathic Surgical Techniques

Published on: October 20, 2023

1.3K

Related Experiment Videos

Last Updated: Jun 7, 2026

A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth
10:50

A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth

Published on: April 8, 2020

9.6K
Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment
07:32

Author Spotlight: 3D Movement Assessment of Maxillary Posterior Teeth in Clear Aligner Treatment

Published on: February 23, 2024

1.1K
Author Spotlight: Development of a Novel Finite Element Analysis Model for Improved Orthognathic Surgical Techniques
07:16

Author Spotlight: Development of a Novel Finite Element Analysis Model for Improved Orthognathic Surgical Techniques

Published on: October 20, 2023

1.3K

Area of Science:

  • Medical Imaging
  • Computer-Aided Surgery
  • Biomedical Engineering

Background:

  • Cone-beam computed tomography (CBCT) provides detailed craniofacial insights for cleft lip and palate (CLP) patients.
  • Manual annotation of CBCT scans for secondary alveolar bone grafting is costly and time-consuming.
  • Existing registration methods struggle with fine-grained variations in CLP defects.

Purpose of the Study:

  • To design and evaluate a novel deformable partial registration method for CLP CBCTs.
  • To enable personalized maxilla completion and accurate cleft defect volume prediction.
  • To reduce the burden of manual annotation in CLP treatment planning.

Main Methods:

  • Proposed an adaptable deep registration framework utilizing cascaded partial registration.
  • Employed maxillary morphology priors and attribute transfer for enhanced accuracy.
  • Developed an adaptable cleft defect mask and volumetric Boolean operators for defect filling.
  • Utilized B-spline deformation for data augmentation to create a synthetic dataset.

Main Results:

  • Achieved state-of-the-art performance in maxilla completion (Dice 0.90 ± 0.02) and cleft defect volume prediction (Dice 0.84 ± 0.04).
  • Demonstrated high accuracy with an average Hausdorff distance of 0.30 ± 0.08 mm for cleft defect estimation.
  • Successfully predicted cleft defect maps consistent with ground truth in challenging unilateral and bilateral CLP cases.

Conclusions:

  • The proposed adaptable deep registration model facilitates patient-specific maxilla completion.
  • Enables automatic annotation of cleft defects, significantly reducing manual effort.
  • Offers a promising solution for improving efficiency and accuracy in CLP treatment planning.