Implementation details and the submission template can be found on the AImageLab GitHub . Supplementary Reading
Research on improving segmentation through advanced labeling techniques presented at CVPR. 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 Implementation details and the submission template can be
"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) Scaling nnU-Net for CBCT Segmentation - arXiv "Segmenting
The subsequent ToothFairy2 challenge (MICCAI 2024) expanded the scope from a single structure to 42 anatomical structures , including the mandible, pharynx, and individual teeth.
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