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

You might also read

Related Articles

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

Sort by
Same author

Ultrastrong to nearly deep-strong magnon-magnon coupling with a high degree of freedom in synthetic antiferromagnets.

Nature communications·2024
Same author

Cu(II)-Catalyzed Enantioselective Aza-Friedel-Crafts Reaction of 1-Naphthols and Electron-Rich Phenols with Isatin-Derived Ketimines.

Chemistry (Weinheim an der Bergstrasse, Germany)·2024
Same author

Extended-Spectrum β-Lactamase-Producing <i>Escherichia coli</i> and <i>Klebsiella pneumoniae</i>: Risk Factors and Economic Burden Among Patients with Bloodstream Infections.

Risk management and healthcare policy·2024
Same author

A novel network pharmacology strategy to decode mechanism of Wuling Powder in treating liver cirrhosis.

Chinese medicine·2024
Same author

Integrative analysis of metabolism subtypes and identification of prognostic metabolism-related genes for glioblastoma.

Bioscience reports·2024
Same author

Nanopore targeted sequencing-based diagnosis of central nervous system infections in HIV-infected patients.

Annals of clinical microbiology and antimicrobials·2024

Related Experiment Video

Updated: Jun 13, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

789

Dental panoramic X-ray image segmentation for multi-feature coordinate position learning.

Tian Ma1, Zhenrui Dang1, Yizhou Yang1

  • 1College of Computer Science and Technology, Xi'an University of Science and Technology, Xi'an,Shaanxi, , China.

Digital Health
|September 16, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel multi-feature coordinate position learning method for accurate tooth segmentation in dental panoramic X-rays. The approach enhances feature details and context, aiding dentists in rapid tooth position assessment.

Keywords:
Tooth segmentationcoordinate attentiondeep learningmulti-feature learning

More Related Videos

Guided Endodontics: Three-Dimensional Planning and Template-Aided Preparation of Endodontic Access Cavities
07:14

Guided Endodontics: Three-Dimensional Planning and Template-Aided Preparation of Endodontic Access Cavities

Published on: May 24, 2022

4.4K
Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
10:23

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

2.7K

Related Experiment Videos

Last Updated: Jun 13, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

789
Guided Endodontics: Three-Dimensional Planning and Template-Aided Preparation of Endodontic Access Cavities
07:14

Guided Endodontics: Three-Dimensional Planning and Template-Aided Preparation of Endodontic Access Cavities

Published on: May 24, 2022

4.4K
Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
10:23

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

2.7K

Area of Science:

  • Medical Imaging
  • Computer Vision
  • Dental Diagnostics

Background:

  • Accurate tooth segmentation in dental panoramic X-rays is crucial for orthodontic and restorative treatment assessment.
  • Challenges include poorly defined interdental boundaries and low contrast between tooth roots and alveolar bone.

Purpose of the Study:

  • To propose a multi-feature coordinate position learning-based method for improved tooth image segmentation.
  • To address the limitations of existing methods in segmenting dental panoramic X-rays.

Main Methods:

  • Data augmentation through horizontal and vertical flipping.
  • Extraction of multi-scale tooth features using residual omni-dimensional dynamic convolution.
  • Complementing boundary features with a two-stream coordinate attention module.
  • Fusion of features to enhance local details and global context.

Main Results:

  • Achieved Intersection over Union (IoU) scores of 87.96% and 92.04%.
  • Attained accuracy (ACC) scores of 97.79% and 97.32%.
  • Reached Dice scores of 86.42% and 95.64% on public datasets.

Conclusions:

  • The proposed network effectively assists clinicians in quickly identifying tooth positions.
  • Validated the efficacy of the feature fusion modules in enhancing segmentation performance.