Artificial intelligence system for automatic maxillary sinus segmentation on cone beam computed tomography images

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. In 101 CBCT scans, MS were annotated using the CranioCatch labelling soft...

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Veröffentlicht in:	Dento-maxillo-facial radiology 2024-04, Vol.53 (4), p.256-266
Hauptverfasser:	Bayrakdar, Ibrahim Sevki, Elfayome, Nermin Sameh, Hussien, Reham Ashraf, Gulsen, Ibrahim Tevfik, Kuran, Alican, Gunes, Ihsan, Al-Badr, Alwaleed, Celik, Ozer, Orhan, Kaan
Format:	Artikel
Sprache:	eng
Schlagworte:	Adult Artificial Intelligence Cone-Beam Computed Tomography - methods Female Humans Male Maxillary Sinus - diagnostic imaging Software
Online-Zugang:	Volltext
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