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.

For a deeper look into the evolving methodology, you may also find these related papers relevant:

Focuses on improving the segmentation of the mandibular canal.

The subsequent ToothFairy2 challenge (MICCAI 2024) expanded the scope from a single structure to 42 anatomical structures , including the mandible, pharynx, and individual teeth.

It utilizes 530 3D volumes (480 public, 50 private) for automated, multi-class 3D segmentation.

Research on improving segmentation through advanced labeling techniques presented at CVPR.

Toothfairy 2.6.2 -

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.

For a deeper look into the evolving methodology, you may also find these related papers relevant: ToothFairy 2.6.2

Focuses on improving the segmentation of the mandibular canal. While the paper above covers the foundation, the

The subsequent ToothFairy2 challenge (MICCAI 2024) expanded the scope from a single structure to 42 anatomical structures , including the mandible, pharynx, and individual teeth. including the mandible

It utilizes 530 3D volumes (480 public, 50 private) for automated, multi-class 3D segmentation.

Research on improving segmentation through advanced labeling techniques presented at CVPR.