Ibrahim Sevki Bayrakdar, Nermin Sameh Elfayome, Reham Ashraf Hussien, Ibrahim Tevfik Gulsen, Alican Kuran, Ihsan Gunes, Alwaleed Al-Badr, Ozer Celik, Kaan Orhan
OBJECTIVES: The study aims to develop an artificial intelligence (AI) model based on nnU-Net v2 for automatic maxillary sinus (MS) segmentation in Cone Beam Computed Tomography (CBCT) volumes and to evaluate the performance of this model. METHODS: In 101 CBCT scans, MS were annotated using the CranioCatch labelling software (Eskisehir, Turkey) The dataset was divided into three parts: 80 CBCT scans for training the model, 11 CBCT scans for model validation, and 10 CBCT scans for testing the model...
March 19, 2024: Dento Maxillo Facial Radiology