3 citations · 9 across the 9 of their papers we have counts for
10 papers
A General-Purpose Dual-Path Interaction Framework for Multi-View Medical Image Segmentation: Alleviating Data Volume Dependency in Small-Sample Regimes
Shuhuan Wang, Yuanyuan Cui, Pengju Wang +10
The performance of medical image segmentation depends on a large amount of annotated data, and most segmentation models experience a significant drop in performance in low-sample-s…
ReMoE: Report-Guided Mixture-of-Experts for Multimodal OCT/OCTA Anomaly Detection
Zihan Nie, Qincheng Qiao, Muhao Xu +4
Multimodal medical anomaly detection identifies samples deviating from normal patterns, where scarce abnormal cases make normality modeling from normal data practical. In retinal O…
CFR-Net:Collaborative Feature Refinement Network for Medical Image Anomaly Detection
Zihan Nie, Muhao Xu, Wei Feng +8
Medical image anomaly detection is central to timely diagnosis and clinical decision support, yet abnormal samples are costly to collect because of disease rarity, privacy concerns…
ESimCSE Unsupervised Contrastive Learning Jointly with UDA Semi-Supervised Learning for Large Label System Text Classification Mode
Ruan Lu, Zhou HangCheng, Ran Meng +4
The challenges faced by text classification with large tag systems in natural language processing tasks include multiple tag systems, uneven data distribution, and high noise. To a…
Universal Semi-Supervised Learning for Medical Image Classification
Lie Ju, Yicheng Wu, Wei Feng +4
Semi-supervised learning (SSL) has attracted much attention since it reduces the expensive costs of collecting adequate well-labeled training data, especially for deep learning met…
3D Matting: A Benchmark Study on Soft Segmentation Method for Pulmonary Nodules Applied in Computed Tomography
Lin Wang, Xiufen Ye, Donghao Zhang +9
Usually, lesions are not isolated but are associated with the surrounding tissues. For example, the growth of a tumour can depend on or infiltrate into the surrounding tissues. Due…
3D Matting: A Soft Segmentation Method Applied in Computed Tomography
Lin Wang, Xiufen Ye, Donghao Zhang +7
Three-dimensional (3D) images, such as CT, MRI, and PET, are common in medical imaging applications and important in clinical diagnosis. Semantic ambiguity is a typical feature of…
Unsupervised Domain Adaptive Fundus Image Segmentation with Category-level Regularization
Wei Feng, Lin Wang, Lie Ju +4
Existing unsupervised domain adaptation methods based on adversarial learning have achieved good performance in several medical imaging tasks. However, these methods focus only on…
AGCN: Augmented Graph Convolutional Network for Lifelong Multi-label Image Recognition
Kaile Du, Fan Lyu, Fuyuan Hu +4
The Lifelong Multi-Label (LML) image recognition builds an online class-incremental classifier in a sequential multi-label image recognition data stream. The key challenges of LML…
Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization
Wei Feng, Lie Ju, Lin Wang +5
Retinal vessel segmentation plays a key role in computer-aided screening, diagnosis, and treatment of various cardiovascular and ophthalmic diseases. Recently, deep learning-based…