Comparison between observer-based and AI-based reading of CBCT datasets: An interrater-reliability study

• Auteurs principaux: Dirk Schulze (Auteur), Lutz Häußermann (Auteur), Julian Ripper (Auteur), Thomas Sottong (Auteur)
• Format: Livre
• Publié: Elsevier, 2024-02-01T00:00:00Z.
• Sujets: article
• Accès en ligne: Connect to this object online.

Objective: To assess the performance of human observers and convolutional neural networks (CNNs) in detecting periodontal lesions in cone beam computed tomography (CBCT), a total of 38 datasets were examined. Three human readers and a CNN-based solution were employed to evaluate the presence of peri...