14 citations · 19 across the 16 of their papers we have counts for
16 papers
Structure-aware Knowledge-guided Heterogeneous Mamba for Zygomaticomaxillary Suture Assessment
Xiaoqi Guo, Birui Chen, Xinquan Yang +8
The Zygomaticomaxillary Suture is a key circummaxillary structure that connects the zygomatic bone and the maxilla, which serves as a primary site of resistance during maxillary ad…
ImplantMamba: Long-range Sequential Modeling Mamba For Dental Implant Position Prediction
Xinquan Yang, Congmin Wang, Xuguang Li +3
In the design of surgical guides for implant placement, determining the precise implant position is a critical step. However, the implant region itself is often characterized by a…
Adaptive Texture-aware Masking for Self-Supervised Learning in 3D Dental CBCT Analysis
Xinquan Yang, Jianfeng Ren, Xuguang Li +4
Cone Beam Computed Tomography (CBCT) is pivotal for 3D diagnostic imaging in dentistry. However, the development of robust AI models for volumetric analysis is often constrained by…
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…
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…
DinoDental: Benchmarking DINOv3 as a Unified Vision Encoder for Dental Image Analysis
Kun Tang, Xinquan Yang, Mianjie Zheng +6
The scarcity and high cost of expert annotations in dental imaging present a significant challenge for the development of AI in dentistry. DINOv3, a state-of-the-art, self-supervis…
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…
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…
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…
Deep Learning Techniques for Automatic Lateral X-ray Cephalometric Landmark Detection: Is the Problem Solved?
Hongyuan Zhang, Ching-Wei Wang, Hikam Muzakky +13
Localization of the craniofacial landmarks from lateral cephalograms is a fundamental task in cephalometric analysis. The automation of the corresponding tasks has thus been the su…
SSAD: Self-supervised Auxiliary Detection Framework for Panoramic X-ray based Dental Disease Diagnosis
Zijian Cai, Xinquan Yang, Xuguang Li +5
Panoramic X-ray is a simple and effective tool for diagnosing dental diseases in clinical practice. When deep learning models are developed to assist dentist in interpreting panora…
Simplify Implant Depth Prediction as Video Grounding: A Texture Perceive Implant Depth Prediction Network
Xinquan Yang, Xuguang Li, Xiaoling Luo +4
Surgical guide plate is an important tool for the dental implant surgery. However, the design process heavily relies on the dentist to manually simulate the implant angle and depth…
TCSloT: Text Guided 3D Context and Slope Aware Triple Network for Dental Implant Position Prediction
Xinquan Yang, Jinheng Xie, Xuechen Li +3
In implant prosthesis treatment, the surgical guide of implant is used to ensure accurate implantation. However, such design heavily relies on the manual location of the implant po…
TCEIP: Text Condition Embedded Regression Network for Dental Implant Position Prediction
Xinquan Yang, Jinheng Xie, Xuguang Li +4
When deep neural network has been proposed to assist the dentist in designing the location of dental implant, most of them are targeting simple cases where only one missing tooth i…
Two-Stream Regression Network for Dental Implant Position Prediction
Xinquan Yang, Xuguang Li, Xuechen Li +4
In implant prosthesis treatment, the design of the surgical guide heavily relies on the manual location of the implant position, which is subjective and prone to doctor's experienc…
ImplantFormer: Vision Transformer based Implant Position Regression Using Dental CBCT Data
Xinquan Yang, Xuguang Li, Xuechen Li +3
Implant prosthesis is the most appropriate treatment for dentition defect or dentition loss, which usually involves a surgical guide design process to decide the implant position.…