Artificial intelligence system for automatic tooth detection and numbering in the mixed dentition in CBCT

Abstract

Aim: To evaluate the effectiveness and accuracy of artificial intelligence (AI) by automating tooth segmentation in CBCT volumes of paediatric patients with mixed dentition, using nnU-Netv2 algorithm.

Background: Identifying and numbering teeth, the initial step in treatment planning, demands an efficient method.

Conclusion: AI models offer a promising approach in the mixed dentition period and play a valuable role in dentists' planning in terms of time and effort.
Read Full Article

I Want to Write a Scientific Research Project

CranioCatch is a global leader in dental medical technology that improves oral care in the field of dentistry. With AI-supported clinical, educational, and labeling solutions, we provide significant improvements in the diagnosis and treatment of dental diseases using contemporary approaches in advanced machine learning technology.

CranioCatch serves thousands of patients with dental health issues worldwide every day with its innovative technologies. That's why we eagerly look forward to meeting our valued dentists who wish to work in the field of 'Scientific Research in Dentistry'.