57 citations · 120 across the 12 of their papers we have counts for
12 papers
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…
FDNet: Feature Decoupled Segmentation Network for Tooth CBCT Image
Xiang Feng, Chengkai Wang, Chengyu Wu +4
Precise Tooth Cone Beam Computed Tomography (CBCT) image segmentation is crucial for orthodontic treatment planning. In this paper, we propose FDNet, a Feature Decoupled Segmentati…
Enhancing Point Annotations with Superpixel and Confidence Learning Guided for Improving Semi-Supervised OCT Fluid Segmentation
Tengjin Weng, Yang Shen, Kai Jin +5
Automatic segmentation of fluid in Optical Coherence Tomography (OCT) images is beneficial for ophthalmologists to make an accurate diagnosis. Although semi-supervised OCT fluid se…
CDNet: Contrastive Disentangled Network for Fine-Grained Image Categorization of Ocular B-Scan Ultrasound
Ruilong Dan, Yunxiang Li, Yijie Wang +5
Precise and rapid categorization of images in the B-scan ultrasound modality is vital for diagnosing ocular diseases. Nevertheless, distinguishing various diseases in ultrasound st…
LViT: Language meets Vision Transformer in Medical Image Segmentation
Zihan Li, Yunxiang Li, Qingde Li +6
Deep learning has been widely used in medical image segmentation and other aspects. However, the performance of existing medical image segmentation models has been limited by the c…
Plug-and-play Shape Refinement Framework for Multi-site and Lifespan Brain Skull Stripping
Yunxiang Li, Ruilong Dan, Shuai Wang +8
Skull stripping is a crucial prerequisite step in the analysis of brain magnetic resonance images (MRI). Although many excellent works or tools have been proposed, they suffer from…
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…
A cascade network for Detecting COVID-19 using chest x-rays
Dailin Lv, Wuteng Qi, Yunxiang Li +2
The worldwide spread of pneumonia caused by a novel coronavirus poses an unprecedented challenge to the world's medical resources and prevention and control measures. Covid-19 atta…
Efficient and Robust Reinforcement Learning with Uncertainty-based Value Expansion
Bo Zhou, Hongsheng Zeng, Fan Wang +2
By integrating dynamics models into model-free reinforcement learning (RL) methods, model-based value expansion (MVE) algorithms have shown a significant advantage in sample effici…