This repository contains the nnU-Net v2.2 network parameters for the segmentation of dento-maxillo-facial CBCT and CT scans with DentalSegmentator model. The evaluation of this model has been published here: DentalSegmentator: robust deep learning-based CBCT image segmentation Please cite our paper and nnU-Net if you use this model for your research : Dot G, et al. DentalSegmentator: robust open source deep learning-based CT and CBCT image segmentation. Journal of Dentistry (2024) doi:10.1016/j.jdent.2024.105130 Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier-Hein KH. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods. 2021;18(2):203-211. doi:10.1038/s41592-020-01008-z Label numbers correspond to the following classes (please refer to the publication for more details) : upper skull mandible upper teeth lower teeth mandibular canal Instructions for how to use the model are provided at: https://github.com/MIC-DKFZ/nnUNet. A 3D Slicer implementation of this model is also available: https://github.com/gaudot/SlicerDentalSegmentator