57 citations · 61 across the 3 of their papers we have counts for
5 papers
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…
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…
AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy
Yunxiang Li, Guodong Zeng, Yifan Zhang +10
Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results wi…
High-Resolution Segmentation of Tooth Root Fuzzy Edge Based on Polynomial Curve Fitting with Landmark Detection
Yunxiang Li, Yifan Zhang, Yaqi Wang +7
As the most economical and routine auxiliary examination in the diagnosis of root canal treatment, oral X-ray has been widely used by stomatologists. It is still challenging to seg…
Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-ray Images
Jingxiong Li, Yaqi Wang, Shuai Wang +4
Coronavirus disease 2019 (COVID-19) is one of the most destructive pandemic after millennium, forcing the world to tackle a health crisis. Automated lung infections classification…