57 citations · 106 across the 18 of their papers we have counts for
18 papers
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…
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…
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…
CTooth+: A Large-scale Dental Cone Beam Computed Tomography Dataset and Benchmark for Tooth Volume Segmentation
Weiwei Cui, Yaqi Wang, Yilong Li +8
Accurate tooth volume segmentation is a prerequisite for computer-aided dental analysis. Deep learning-based tooth segmentation methods have achieved satisfying performances but re…
DU-Net based Unsupervised Contrastive Learning for Cancer Segmentation in Histology Images
Yilong Li, Yaqi Wang, Huiyu Zhou +3
In this paper, we introduce an unsupervised cancer segmentation framework for histology images. The framework involves an effective contrastive learning scheme for extracting disti…
CTooth: A Fully Annotated 3D Dataset and Benchmark for Tooth Volume Segmentation on Cone Beam Computed Tomography Images
Weiwei Cui, Yaqi Wang, Qianni Zhang +5
3D tooth segmentation is a prerequisite for computer-aided dental diagnosis and treatment. However, segmenting all tooth regions manually is subjective and time-consuming. Recently…
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…
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…
Magnification-independent Histopathological Image Classification with Similarity-based Multi-scale Embeddings
Yibao Sun, Xingru Huang, Yaqi Wang +2
The classification of histopathological images is of great value in both cancer diagnosis and pathological studies. However, multiple reasons, such as variations caused by magnific…
SRPN: similarity-based region proposal networks for nuclei and cells detection in histology images
Yibao Sun, Xingru Huang, Huiyu Zhou +1
The detection of nuclei and cells in histology images is of great value in both clinical practice and pathological studies. However, multiple reasons such as morphological variatio…
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…
Multimodal Gait Recognition for Neurodegenerative Diseases
Aite Zhao, Jianbo Li, Junyu Dong +5
In recent years, single modality based gait recognition has been extensively explored in the analysis of medical images or other sensory data, and it is recognised that each of the…
Perceptual underwater image enhancement with deep learning and physical priors
Long Chen, Zheheng Jiang, Lei Tong +5
Underwater image enhancement, as a pre-processing step to improve the accuracy of the following object detection task, has drawn considerable attention in the field of underwater n…
Deep Learning Based Brain Tumor Segmentation: A Survey
Zhihua Liu, Lei Tong, Zheheng Jiang +6
Brain tumor segmentation is one of the most challenging problems in medical image analysis. The goal of brain tumor segmentation is to generate accurate delineation of brain tumor…
CANet: Context Aware Network for 3D Brain Glioma Segmentation
Zhihua Liu, Lei Tong, Long Chen +7
Automated segmentation of brain glioma plays an active role in diagnosis decision, progression monitoring and surgery planning. Based on deep neural networks, previous studies have…
Cost-sensitive Boosting Pruning Trees for depression detection on Twitter
Lei Tong, Zhihua Liu, Zheheng Jiang +9
Depression is one of the most common mental health disorders, and a large number of depressed people commit suicide each year. Potential depression sufferers usually do not consult…