Toothfairy 2.6.2 -

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

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

"Segmenting the Inferior Alveolar Canal in CBCTs Volumes: the ToothFairy Challenge" Journal: IEEE Transactions on Medical Imaging (2024) Key Authors: Federico Bolelli, Luca Lumetti, et al. Core Content: This paper details the first challenge (ToothFairy), including the dataset of 443 CBCT scans and a comprehensive comparative evaluation of segmentation methods for the Inferior Alveolar Canal (IAC). Key Technical Components (Version 2.6.2 Context) ToothFairy 2.6.2

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

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. It utilizes 530 3D volumes (480 public, 50

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. Key Technical Components (Version 2

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