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eess.IV2023
3D-U-SAM Network For Few-shot Tooth Segmentation in CBCT Images
Yifu Zhang, Zuozhu Liu, Yang Feng +1
Accurate representation of tooth position is extremely important in treatment. 3D dental image segmentation is a widely used method, however labelled 3D dental datasets are a scarc…
eess.IV2023
ToothSegNet: Image Degradation meets Tooth Segmentation in CBCT Images
Jiaxiang Liu, Tianxiang Hu, Yang Feng +2
In computer-assisted orthodontics, three-dimensional tooth models are required for many medical treatments. Tooth segmentation from cone-beam computed tomography (CBCT) images is a…
eess.IV2022
AI-enabled Automatic Multimodal Fusion of Cone-Beam CT and Intraoral Scans for Intelligent 3D Tooth-Bone Reconstruction and Clinical Applications
Jin Hao, Jiaxiang Liu, Jin Li +17
A critical step in virtual dental treatment planning is to accurately delineate all tooth-bone structures from CBCT with high fidelity and accurate anatomical information. Previous…