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

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...

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Hoofdauteurs: Dirk Schulze (Auteur), Lutz Häußermann (Auteur), Julian Ripper (Auteur), Thomas Sottong (Auteur)
Formaat: Boek
Gepubliceerd in: Elsevier, 2024-02-01T00:00:00Z.
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