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

Tooth Anatomy01:21

Tooth Anatomy

594
The human tooth enables us to eat a variety of foods, speak clearly, and even aid in shaping our faces. Teeth are composed of various elements that work together. Here's a detailed look at the anatomy of a human tooth.
The Crown, Neck, and Root
The visible part of the tooth is referred to as the crown. It's covered by enamel, the hardest substance in the human body. The crown is uniquely shaped for each type of tooth, allowing for different functions such as cutting, tearing, or...
594

You might also read

Related Articles

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

Sort by
Same author

Electric vs Manual Toothbrushing Effects on QLF-Assessed Plaque in Smokers and Non-Smokers: A 24-Week RCT.

International dental journal·2026
Same author

Resveratrol in Oral Squamous Cell Carcinoma: Preclinical Evidence and Translational Opportunities.

Oncology research·2026
Same author

Xenobiotic Sulforaphane in Head and Neck Cancer: Beyond the Nrf2 Pathway.

Journal of xenobiotics·2026
Same author

Minimally Invasive (MINST) Versus Conventional Non-Surgical Therapy for Residual Pockets in Patients With Periodontitis: A Randomized Clinical Trial.

Journal of periodontal research·2026
Same author

Comparing the Effect of Scaling and Polishing on Nine Oral Health and Dental Aesthetic Measures between Current and Never Smokers from the SMILE Study Cohort.

Journal of dentistry·2026
Same author

Orthodontic Treatment in Idiopathic Root Resorption: A Narrative Review and a Clinical Case Report.

Journal of clinical medicine·2026

Related Experiment Video

Updated: Jul 31, 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

904

Tooth automatic segmentation from CBCT images: a systematic review.

Alessandro Polizzi1,2, Vincenzo Quinzi3, Vincenzo Ronsivalle4

  • 1Department of General Surgery and Surgical-Medical Specialties, School of Dentistry, University of Catania, AOU "Policlinico-San Marco", Via S. Sofia 78, 95124, Catania, Italy. alexpoli345@gmail.com.

Clinical Oral Investigations
|May 6, 2023
PubMed
Summary

Convolutional Neural Networks (CNNs) show the most promise for automatic tooth segmentation in 3D CBCT images, outperforming traditional methods. These advanced deep learning techniques address key limitations in digital dentistry.

Keywords:
AutomaticCBCTDeep learningDigitalTooth segmentation

More Related Videos

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

9.7K
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.8K

Related Experiment Videos

Last Updated: Jul 31, 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

904
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

9.7K
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.8K

Area of Science:

  • Radiology and Dental Imaging
  • Artificial Intelligence in Medicine
  • Medical Image Analysis

Background:

  • Accurate tooth segmentation from 3D Cone-Beam Computed Tomography (CBCT) is crucial for digital dentistry applications.
  • Existing segmentation methods face challenges including root anatomy variations, image artifacts, and time constraints.

Approach:

  • A comprehensive literature search was conducted in March 2023 across major scientific databases (PubMed, Scopus, Web of Science, IEEE Explore).
  • The review included various study types published in English, focusing on technological advances in automatic tooth segmentation from CBCT images.

Key Points:

  • Deep learning, particularly Convolutional Neural Networks (CNNs), emerged as the dominant and most effective approach.
  • The Dice similarity index was the primary evaluation metric, with reported ranges from 90% ± 3% to 97.9% ± 1.5%.
  • Traditional methods like thresholding were found to be unreliable for accurate tooth segmentation.

Conclusions:

  • CNNs demonstrate superior performance and reliability for automatic tooth segmentation in CBCT images.
  • CNNs offer a promising solution to overcome limitations such as heavy scattering, metal artifacts, and immature teeth.
  • Further research with standardized protocols and evaluation metrics is recommended to objectively compare deep learning architectures.