11 - A standard automated assessment tool for craniofacial landmarks in CBCT: InVivo7 software

Abstract

Background

In craniofacial analysis, artificial intelligence (AI)-driven algorithms facilitate the precise identification of anatomical landmarks on Cone Beam Computed Tomography (CBCT) scans.

Objectives

This study investigates the functionality of the three-dimensional imaging software InVivo7, assessing its potential as an automated tool for craniofacial landmark identification in CBCT scans.

Methods

AI-assisted automatic landmark tracing in InVivo7 was employed to identify anatomical landmarks in CBCT images. Each landmark was manually verified by a skilled evaluator to ensure accuracy, particularly for soft tissue markers and dental measurements, which often presented challenges for AI detection. The study utilized a standardized cephalometric analysis to compare the software’s performance. The evaluation included assessing the software's ability to recognize skeletal, dental, and soft tissue structures accurately.

Results

The AI-enhanced software demonstrated high precision in identifying craniofacial landmarks, with manual verification confirming its reliability, leading to the subsequent creation of a customized automated configuration for orthodontic diagnosis and treatment outcome evaluation. Specific clinical measures, such as the facial plane angle and molar relationships, were calculated using established formulas, allowing the software to categorize molar relationship classes (Angle Class I, II, III).

Conclusions

InVivo7 presents a reliable and efficient tool for craniofacial landmark analysis, enhancing diagnostic accuracy while reducing manual labor. Ongoing validation and software updates are essential to fully optimize its clinical applicability and ensure consistent performance across diverse patient populations.