This is the official code for "GEPAR3D: Geometry Prior-Assisted Learning for 3D Tooth Segmentation" accepted for the 28th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2025.
Complete code comming soon.
Datasets related to this paper:
- https://www.nature.com/articles/s41467-022-29637-2 (Z.Cui et al.)
- https://zenodo.org/records/15739014 (GEPAR3D T.Szczepański et al.)
- https://ditto.ing.unimore.it/toothfairy2/ (Bolelli et al.)
- configs/data_split.json - exact patient IDS used for evaluation
- configs/experiment_config.yaml - configuration for experiments: table 1 and table 2
- configs/requirements.yaml - conda environment configuration
- scripts/ablation_study/train.py - script to train all experiments of ablation study, including proposed solution
- scripts/ablation_study/inference.py - script to run inference of models within ablation study, including proposed solution
- scripts/general_segmentation_methods/train.py - script to train all general segmentation methods, table 1