14 citations · 22 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis
Jiaxiang Liu, Tianxiang Hu, Yan Zhang +3
Zero-shot medical image classification is a critical process in real-world scenarios where we have limited access to all possible diseases or large-scale annotated data. It involve…
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…
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…