85 citations · 273 across the 108 of their papers we have counts for
9 papers · 1 filter
Which Pixel to Annotate: a Label-Efficient Nuclei Segmentation Framework
Wei Lou, Haofeng Li, Guanbin Li +2
Recently deep neural networks, which require a large amount of annotated samples, have been widely applied in nuclei instance segmentation of H\&E stained pathology images. However…
BoxPolyp:Boost Generalized Polyp Segmentation Using Extra Coarse Bounding Box Annotations
Jun Wei, Yiwen Hu, Guanbin Li +3
Accurate polyp segmentation is of great importance for colorectal cancer diagnosis and treatment. However, due to the high cost of producing accurate mask annotations, existing pol…
Attentive Symmetric Autoencoder for Brain MRI Segmentation
Junjia Huang, Haofeng Li, Guanbin Li +1
Self-supervised learning methods based on image patch reconstruction have witnessed great success in training auto-encoders, whose pre-trained weights can be transferred to fine-tu…
Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge
Zhihong Chen, Guanbin Li, Xiang Wan
Medical vision-and-language pre-training (Med-VLP) has received considerable attention owing to its applicability to extracting generic vision-and-language representations from med…
Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training
Zhihong Chen, Yuhao Du, Jinpeng Hu +4
Medical vision-and-language pre-training provides a feasible solution to extract effective vision-and-language representations from medical images and texts. However, few studies h…
Less is More: Adaptive Curriculum Learning for Thyroid Nodule Diagnosis
Haifan Gong, Hui Cheng, Yifan Xie +4
Thyroid nodule classification aims at determining whether the nodule is benign or malignant based on a given ultrasound image. However, the label obtained by the cytological biopsy…
BCNet: Bronchus Classification via Structure Guided Representation Learning
Wenhao Huang, Haifan Gong, Huan Zhang +5
CT-based bronchial tree analysis is essential for diagnosing lung and airway diseases, yet automatic bronchus classification remains challenging because bronchial topology varies s…
X-Trans2Cap: Cross-Modal Knowledge Transfer using Transformer for 3D Dense Captioning
Zhihao Yuan, Xu Yan, Yinghong Liao +4
3D dense captioning aims to describe individual objects by natural language in 3D scenes, where 3D scenes are usually represented as RGB-D scans or point clouds. However, only expl…
Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image Segmentation
Xinkai Zhao, Chaowei Fang, De-Jun Fan +3
Semi-supervised learning (SSL), which aims at leveraging a few labeled images and a large number of unlabeled images for network training, is beneficial for relieving the burden of…