Creating and Testing a New Computer Vision System for Detecting Dental Problems in Orthodontic Patients.

Abstract

The research project focuses on the creation and assessment of an innovative computer vision system designed to identify dental irregularities in individuals undergoing orthodontic treatment. To establish the computer vision system, a comprehensive dataset of dental images was collected, encompassing various orthodontic cases. The system's algorithm was trained to recognize patterns indicative of common dental anomalies, such as malocclusions, spacing issues, and misalignments. Rigorous testing and refinement of the algorithm were conducted to enhance its accuracy and reliability. The validation of the system was carried out using the dental records and images of the 40 patients. The computer vision system's performance was evaluated against assessments made by experienced orthodontists. The results demonstrated a commendable level of concurrence between the system's automated detections and the orthodontists' evaluations, suggesting its potential as a valuable diagnostic tool. In conclusion, the development and validation of this novel computer vision system exhibit promising outcomes in its ability to automatically detect dental anomalies in orthodontic patients.