Self-Supervised Learning with Masked Autoencoders for Teeth Segmentation from Intra-oral 3D Scans
Author:
Affiliation:
1. Temple University,Department of Computer and Information Sciences,Philadelphia,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10483279/10483282/10484240.pdf?arnumber=10484240
Reference54 articles.
1. Enhanced Masked Image Modeling for Analysis of Dental Panoramic Radiographs
2. Self-Supervised Learning with Masked Image Modeling for Teeth Numbering, Detection of Dental Restorations, and Instance Segmentation in Dental Panoramic Radiographs
3. Beit: Bert pre-training of image transformers;Bao,2021
4. Teeth3ds: a benchmark for teeth segmentation and labeling from intra-oral 3d scans;Ben-Hamadou,2022
5. TSegNet: An efficient and accurate tooth segmentation network on 3D dental model
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