Tooth segmentation on multimodal images using adapted segment anything model
Abstract With the increase in dental patient numbers and the ongoing digital transformation of dental hospitals, tooth segmentation has become increasingly crucial for the digital diagnosis, design, treatment, and customized appliance manufacturing of orthodontics, oral implant surgery, and prosthod...
Saved in:
| Main Authors: | Peijuan Wang, Hanjie Gu, Yuliang Sun |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-96301-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
SAM2Former: Segment Anything Model 2 Assisting UNet-Like Transformer for Remote Sensing Image Semantic Segmentation
by: Xuewen Li, et al.
Published: (2025-01-01) -
Research on Medical Image Segmentation Based on SAM and Its Future Prospects
by: Kangxu Fan, et al.
Published: (2025-06-01) -
Approach to Enhancing Panoramic Segmentation in Indoor Construction Sites Based on a Perspective Image Segmentation Foundation Model
by: Juho Han, et al.
Published: (2025-04-01) -
Pre‐trained SAM as data augmentation for image segmentation
by: Junjun Wu, et al.
Published: (2025-02-01) -
BCTDNet: Building Change-Type Detection Networks with the Segment Anything Model in Remote Sensing Images
by: Wei Zhang, et al.
Published: (2025-08-01)