While the paper above covers the foundation, the versioning likely refers to a specific iteration of the dataset or the nnU-Net implementation used for the challenge.
Implementation details and the submission template can be found on the AImageLab GitHub . Supplementary Reading ToothFairy 2.6.2
The subsequent ToothFairy2 challenge (MICCAI 2024) expanded the scope from a single structure to 42 anatomical structures , including the mandible, pharynx, and individual teeth. While the paper above covers the foundation, the
It utilizes 530 3D volumes (480 public, 50 private) for automated, multi-class 3D segmentation. It utilizes 530 3D volumes (480 public, 50
The primary "complete paper" summarizing the core research and evaluation for the ToothFairy series is:
A technical report on the specific network topology (6 resolution stages) and normalization used in the ToothFairy2 dataset. Scaling nnU-Net for CBCT Segmentation - arXiv
For a deeper look into the evolving methodology, you may also find these related papers relevant: