activity
20202025
most citedGT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation

57 citations · 75 across the 9 of their papers we have counts for

collaborators

12 papers

cs.CV2025

MICCAI STSR 2025 Challenge: Semi-Supervised Teeth and Pulp Segmentation and CBCT-IOS Registration

Yaqi Wang, Zhi Li, Chengyu Wu +15

Cone-Beam Computed Tomography (CBCT) and Intraoral Scanning (IOS) are essential for digital dentistry, but annotated data scarcity limits automated solutions for pulp canal segment…

eess.IV2025

MICCAI STS 2024 Challenge: Semi-Supervised Instance-Level Tooth Segmentation in Panoramic X-ray and CBCT Images

Yaqi Wang, Zhi Li, Chengyu Wu +19

Orthopantomogram (OPGs) and Cone-Beam Computed Tomography (CBCT) are vital for dentistry, but creating large datasets for automated tooth segmentation is hindered by the labor-inte…

cs.CV20243 cited

STS MICCAI 2023 Challenge: Grand challenge on 2D and 3D semi-supervised tooth segmentation

Yaqi Wang, Yifan Zhang, Xiaodiao Chen +24

Computer-aided design (CAD) tools are increasingly popular in modern dental practice, particularly for treatment planning or comprehensive prognosis evaluation. In particular, the…

cs.CV20212 cited

Dispensed Transformer Network for Unsupervised Domain Adaptation

Yunxiang Li, Jingxiong Li, Ruilong Dan +10

Accurate segmentation is a crucial step in medical image analysis and applying supervised machine learning to segment the organs or lesions has been substantiated effective. Howeve…

cs.CV202157 cited

GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation

Yunxiang Li, Shuai Wang, Jun Wang +5

To achieve an accurate assessment of root canal therapy, a fundamental step is to perform tooth root segmentation on oral X-ray images, in that the position of tooth root boundary…

eess.IV20211 cited

Structure-aware scale-adaptive networks for cancer segmentation in whole-slide images

Yibao Sun, Giussepi Lopez, Yaqi Wang +3

Cancer segmentation in whole-slide images is a fundamental step for viable tumour burden estimation, which is of great value for cancer assessment. However, factors like vague boun…