Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

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

How do lower-limb landmarking errors impact morphometrics in total knee arthroplasty planning?

European journal of radiology·2026

Same author

A Clinically Compatible Method for Generating Preoperative Finite Element Models to Simulate Facial Appearance and Movements in Orthognathic Surgery.

International journal for numerical methods in biomedical engineering·2026

Same author

Finite element modelling of the sacral soft tissues under compressive loading in the context of pressure ulcer prevention: importance of the personalization of the material parameters.

Clinical biomechanics (Bristol, Avon)·2025

Same author

The G-OBIM tongue model: An accurate open-source biomechanical model of a male human tongue.

PLoS computational biology·2025

Same author

Accuracy evaluation of an automatic landmarking method based on 3D segmented CT scans of full lower limbs with knee osteoarthritis.

European journal of radiology·2025

Same author

Forward to the special issue on biomechanics of breast tissues and its clinical applications.

Clinical biomechanics (Bristol, Avon)·2024

Search research articles

Related Experiment Video

Updated: Jul 16, 2026

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

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

Published on: August 5, 2021

3D statistical models for tooth surface reconstruction.

Stéphanie I Buchaillard¹, S H Ong, Yohan Payan

¹Department of Electrical and Computer Engineering, National University of Singapore, Singapore.

Computers in Biology and Medicine

|March 6, 2007

Summary

This study introduces a novel method for 3D tooth surface reconstruction using statistical shape models. The technique efficiently recovers tooth shape from partial crown data, advancing dental imaging capabilities.

More Related Videos

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

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

Published on: May 24, 2022

Measuring Maxillary Posterior Tooth Movement: A Model Assessment using Palatal and Dental Superimposition

Measuring Maxillary Posterior Tooth Movement: A Model Assessment using Palatal and Dental Superimposition

Published on: February 23, 2024

Related Experiment Videos

Last Updated: Jul 16, 2026

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

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

Published on: August 5, 2021

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

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

Published on: May 24, 2022

Measuring Maxillary Posterior Tooth Movement: A Model Assessment using Palatal and Dental Superimposition

Measuring Maxillary Posterior Tooth Movement: A Model Assessment using Palatal and Dental Superimposition

Published on: February 23, 2024

Area of Science:

Biomedical Engineering
Computer-Aided Surgery
Dental Technology

Background:

Accurate 3D tooth reconstruction is crucial for various dental applications, including diagnostics, treatment planning, and prosthodontics.
Existing methods may struggle with partial or incomplete shape data, necessitating robust reconstruction techniques.

Purpose of the Study:

To develop and present an efficient method for reconstructing the complete 3D surface of a tooth from limited shape information.
To utilize a statistical shape model for accurate and automated tooth surface recovery.

Main Methods:

A statistical shape model was created offline from a dataset of tooth specimens, defining a mean shape and deformation modes.
During reconstruction, rigid registration aligns the mean shape to the target partial data.
Iterative surface deformation minimizes distance errors, guided by the statistical model's deformation modes to approximate the full tooth shape.

Main Results:

The proposed method demonstrated efficiency in reconstructing the 3D tooth surface.
Successful recovery of tooth shape was achieved even with partial crown information.
The statistical model effectively guided the deformation process for accurate surface approximation.

Conclusions:

The presented statistical shape model-based approach offers an efficient solution for 3D tooth reconstruction from partial data.
This method holds potential for improving digital dentistry workflows and enhancing the accuracy of dental restorations.