collaborators

5 papers

cs.CV2026

Caries DETR: Tooth Structure-aware Prior and Lesion-aware Dynamic Loss Refinement for DETR Based Caries Detection

Xuefen Liu, Xinquan Yang, Mianjie Zheng +5

As dental caries appear as subtle, low-contrast lesions in intraoral imaging, existing deep learning models face significant challenges in the early detection of caries. While rece…

cs.CV2026

Text-Conditioned Multi-Expert Regression Framework for Fully Automated Multi-Abutment Design

Mianjie Zheng, Xinquan Yang, Xuefen Liu +4

Dental implant abutments serve as the geometric and biomechanical interface between the implant fixture and the prosthetic crown, yet their design relies heavily on manual effort a…

cs.CV2026

RegFreeNet: A Registration-Free Network for CBCT-based 3D Dental Implant Planning

Xinquan Yang, Xuguang Li, Mianjie Zheng +6

As the commercial surgical guide design software usually does not support the export of implant position for pre-implantation data, existing methods have to scan the post-implantat…

cs.CV2025

SSA3D: Text-Conditioned Assisted Self-Supervised Framework for Automatic Dental Abutment Design

Mianjie Zheng, Xinquan Yang, Along He +6

Abutment design is a critical step in dental implant restoration. However, manual design involves tedious measurement and fitting, and research on automating this process with AI i…

cs.CV2025

Text Condition Embedded Regression Network for Automated Dental Abutment Design

Mianjie Zheng, Xinquan Yang, Xuguang Li +5

The abutment is an important part of artificial dental implants, whose design process is time-consuming and labor-intensive. Long-term use of inappropriate dental implant abutments…