Automatic segmentation of the maxillary sinus on cone beam computed tomographic images with U-Net deep learning model.

Busra Ozturk Yavuz Selim Taspinar Murat Koklu Melek Tassoker

Published in: European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery (2024)

The U-Net model has shown high success in maxillary sinus segmentation. In this way, fast and highly accurate evaluations are possible, saving time by reducing the workload of clinicians and eliminating subjective errors.

Keyphrases

deep learning
convolutional neural network
artificial intelligence
cone beam
machine learning
high resolution
emergency department
cone beam computed tomography
mass spectrometry
physical activity
sleep quality
optical coherence tomography