11 citations · 13 across the 5 of their papers we have counts for
5 papers
Human-machine Interactive Tissue Prototype Learning for Label-efficient Histopathology Image Segmentation
Wentao Pan, Jiangpeng Yan, Hanbo Chen +4
Recently, deep neural networks have greatly advanced histopathology image segmentation but usually require abundant annotated data. However, due to the gigapixel scale of whole sli…
ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images
Jiawei Yang, Hanbo Chen, Yuan Liang +3
Detectingandsegmentingobjectswithinwholeslideimagesis essential in computational pathology workflow. Self-supervised learning (SSL) is appealing to such annotation-heavy tasks. Des…
ReMix: A General and Efficient Framework for Multiple Instance Learning based Whole Slide Image Classification
Jiawei Yang, Hanbo Chen, Yu Zhao +4
Whole slide image (WSI) classification often relies on deep weakly supervised multiple instance learning (MIL) methods to handle gigapixel resolution images and slide-level labels.…
Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction
Jiangpeng Yan, Chenghui Yu, Hanbo Chen +4
Recently, deep neural networks have greatly advanced undersampled Magnetic Resonance Image (MRI) reconstruction, wherein most studies follow the one-anatomy-one-network fashion, i.…
Towards better understanding and better generalization of few-shot classification in histology images with contrastive learning
Jiawei Yang, Hanbo Chen, Jiangpeng Yan +2
Few-shot learning is an established topic in natural images for years, but few work is attended to histology images, which is of high clinical value since well-labeled datasets and…