Dear All,
We are glad to announce the availability of DentalSegmentator, a new 3D Slicer extension for automatic segmentation of dental CT and CBCT scans. It is now available in the latest Slicer 5.7.0 preview release.
This tool is based on a nnU-Net model trained and evaluated on more than 700 CT and CBCT scans. It has been shown to be robust in most situations, even in the presence of metallic artefacts or varying field of views.
It generates the following segmentations :
- Maxilla & Upper Skull
- Mandible
- Upper Teeth
- Lower Teeth
- Mandibular canal
Segment editor tools and model export features are directly available in the module. The extension does not require a GPU, but a CUDA-capable GPU is needed for fast results (around 1-2 minutes).
Install tutorial and demonstration video:
If you use DentalSegmentator for your work, please cite our paper and nnU-Net:
Dot G, Chaurasia A, Dubois G, et al. DentalSegmentator: robust deep learning-based CBCT image segmentation. Published online March 18, 2024:2024.03.18.24304458. doi:10.1101/2024.03.18.24304458
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
The module was developed by T. Pelletier and R. Fenioux (Kitware SAS); financed by the FFO (Fédération Française d’Orthodontie) and the Fondation des Gueules Cassées.