94 citations · 291 across the 30 of their papers we have counts for
9 papers · 1 filter
Enhancing Sample Utilization through Sample Adaptive Augmentation in Semi-Supervised Learning
Guan Gui, Zhen Zhao, Lei Qi +3
In semi-supervised learning, unlabeled samples can be utilized through augmentation and consistency regularization. However, we observed certain samples, even undergoing strong aug…
R2GenGPT: Radiology Report Generation with Frozen LLMs
Zhanyu Wang, Lingqiao Liu, Lei Wang +1
Large Language Models (LLMs) have consistently showcased remarkable generalization capabilities when applied to various language tasks. Nonetheless, harnessing the full potential o…
Rethinking Data Perturbation and Model Stabilization for Semi-supervised Medical Image Segmentation
Zhen Zhao, Ye Liu, Meng Zhao +3
Studies on semi-supervised medical image segmentation (SSMIS) have seen fast progress recently. Due to the limited labelled data, SSMIS methods mainly focus on effectively leveragi…
Contrastive Diffusion Model with Auxiliary Guidance for Coarse-to-Fine PET Reconstruction
Zeyu Han, Yuhan Wang, Luping Zhou +5
To obtain high-quality positron emission tomography (PET) scans while reducing radiation exposure to the human body, various approaches have been proposed to reconstruct standard-d…
Towards Semi-supervised Learning with Non-random Missing Labels
Yue Duan, Zhen Zhao, Lei Qi +3
Semi-supervised learning (SSL) tackles the label missing problem by enabling the effective usage of unlabeled data. While existing SSL methods focus on the traditional setting, a p…
Automatic Radiology Report Generation by Learning with Increasingly Hard Negatives
Bhanu Prakash Voutharoja, Lei Wang, Luping Zhou
Automatic radiology report generation is challenging as medical images or reports are usually similar to each other due to the common content of anatomy. This makes a model hard to…
Learning Partial Correlation based Deep Visual Representation for Image Classification
Saimunur Rahman, Piotr Koniusz, Lei Wang +3
Visual representation based on covariance matrix has demonstrates its efficacy for image classification by characterising the pairwise correlation of different channels in convolut…
METransformer: Radiology Report Generation by Transformer with Multiple Learnable Expert Tokens
Zhanyu Wang, Lingqiao Liu, Lei Wang +1
In clinical scenarios, multi-specialist consultation could significantly benefit the diagnosis, especially for intricate cases. This inspires us to explore a "multi-expert joint di…
Neural Vector Fields: Implicit Representation by Explicit Learning
Xianghui Yang, Guosheng Lin, Zhenghao Chen +1
Deep neural networks (DNNs) are widely applied for nowadays 3D surface reconstruction tasks and such methods can be further divided into two categories, which respectively warp tem…