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Updated: Sep 18, 2025

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

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Intelligent Virtual Dental Implant Placement via 3D Segmentation Strategy.

G Cai¹, B Wen², Z Gong¹

¹Hospital of Stomatology, Guanghua School of Stomatology, Guangdong Provincial Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, China.

Journal of Dental Research

|June 24, 2025

Summary

This summary is machine-generated.

This study introduces an AI tool for automated virtual dental implant placement using 3D segmentation of cone-beam computed tomography (CBCT) scans. The AI tool accurately predicts implant dimensions and position, aiding digital implant surgery planning.

Keywords:

artificial intelligence computer-assisted surgery cone-beam computed tomography decision making deep learning dental prosthesis

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Dynamic Navigation for Dental Implant Placement

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Published on: September 13, 2022

Area of Science:

Dentistry
Medical Imaging
Artificial Intelligence

Background:

Virtual dental implant placement from cone-beam computed tomography (CBCT) is crucial for digital implant surgery.
Manual placement is complex, requiring balancing restoration orientation, bone adaptation, and anatomical safety.
Automating this process efficiently presents significant challenges.

Purpose of the Study:

To develop an intelligent virtual dental implant placement system using a 3D segmentation strategy.
To automate the generation of virtual implants from CBCT data for missing mandibular first molars.

Main Methods:

A segmentation module based on nnU-Net was developed to generate virtual implants from CBCT scans.
An approximation module was employed for mathematical optimization to meet clinical requirements.
The system was trained and tested on 190 CBCT scans from four centers.

Main Results:

The AI tool achieved high segmentation accuracy with a surface Dice coefficient (sDice) of 0.903 (internal) and 0.884 (external).
Average deviations from ground truth were minimal for implant platform (0.82-0.85 mm), apex (1.44-1.47 mm), and angle (4.9-5.5°).
The tool demonstrated strong performance in predicting virtual implant dimensions and position.

Conclusions:

The 3D segmentation-based AI tool shows excellent performance in virtual dental implant placement.
This technology has significant potential for clinical application in digital implant surgery planning.
The automated approach addresses the complexity of manual implant placement, improving efficiency and accuracy.