9 citations · 18 across the 13 of their papers we have counts for
6 papers · 1 filter
HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency Regularization
Zijie Fang, Yifeng Wang, Peizhang Xie +2
Tissue semantic segmentation is one of the key tasks in computational pathology. To avoid the expensive and laborious acquisition of pixel-level annotations, a wide range of studie…
Multimodal Cross-Task Interaction for Survival Analysis in Whole Slide Pathological Images
Songhan Jiang, Zhengyu Gan, Linghan Cai +2
Survival prediction, utilizing pathological images and genomic profiles, is increasingly important in cancer analysis and prognosis. Despite significant progress, precise survival…
Dynamic Pseudo Label Optimization in Point-Supervised Nuclei Segmentation
Ziyue Wang, Ye Zhang, Yifeng Wang +2
Deep learning has achieved impressive results in nuclei segmentation, but the massive requirement for pixel-wise labels remains a significant challenge. To alleviate the annotation…
DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation via Cross-Task Interactions
Ye Zhang, Yifeng Wang, Zijie Fang +4
Weakly supervised segmentation methods have gained significant attention due to their ability to reduce the reliance on costly pixel-level annotations during model training. Howeve…
MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models
Zijie Fang, Yifeng Wang, Ye Zhang +4
Recently, pathological diagnosis has achieved superior performance by combining deep learning models with the multiple instance learning (MIL) framework using whole slide images (W…
Boundary-aware Contrastive Learning for Semi-supervised Nuclei Instance Segmentation
Ye Zhang, Ziyue Wang, Yifeng Wang +5
Semi-supervised segmentation methods have demonstrated promising results in natural scenarios, providing a solution to reduce dependency on manual annotation. However, these method…