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DentalSegmentator: Robust open source deep learning-based CT and CBCT image segmentation
Gauthier Dot1, Akhilanand Chaurasia2, Guillaume Dubois3
1UFR Odontologie, Universite Paris Cité, Paris, France; Service de Medecine Bucco-Dentaire, AP-HP, Hopital Pitie-Salpetriere, Paris, France; Institut de Biomecanique Humaine Georges Charpak, Arts et Metiers Institute of Technology, Paris, France.
A new open-source tool, DentalSegmentator, offers fully automatic segmentation of key anatomical structures in dento-maxillo-facial (DMF) CT and CBCT scans. This robust software provides accurate 3D models for digital dentistry workflows.
Area of Science:
- Digital dentistry
- Medical imaging analysis
- 3D reconstruction
Background:
- Accurate segmentation of anatomical structures in dento-maxillo-facial (DMF) computed tomography (CT) and cone beam computed tomography (CBCT) scans is crucial for digital dentistry.
- Existing methods may lack automation or robustness, hindering widespread clinical adoption.
Purpose of the Study:
- To introduce and evaluate DentalSegmentator, a novel open-source tool for fully automatic segmentation of five critical anatomical structures on DMF CT and CBCT scans.
- To assess the performance and generalizability of DentalSegmentator across diverse datasets.
Main Methods:
- A retrospective dataset of 470 CT and CBCT scans was used for training and validation.
- The tool's performance was evaluated on an internal dataset (133 scans) and an external dataset (123 scans) by comparing automatic segmentations with expert segmentations.
- Key performance metrics included Dice Similarity Coefficient (DSC) and Normalized Surface Distance (NSD).
Main Results:
- High accuracy was achieved, with mean overall DSC of 92.2% on the internal dataset and 94.2% on the external dataset.
- Mean overall NSD was 98.2% on the internal dataset and 98.4% on the external dataset, indicating precise surface distance.
- The results demonstrate robust multiclass segmentation capabilities across a diverse range of DMF CT and CBCT scans.
Conclusions:
- DentalSegmentator provides a fully automatic, robust, and accurate solution for segmenting anatomical structures in DMF CT and CBCT scans.
- The open-source tool, available as a 3D Slicer extension, facilitates the creation of patient-specific 3D models for various digital dentistry applications.
- This approach supports visualization, treatment planning, and intervention in clinical practice.
