151 citations · 205 across the 8 of their papers we have counts for
6 papers · 1 filter
End-to-End Cell Detection via Instance-aware Graph Modeling
Ruochen Liu, Yalin Zheng, Jingxin Liu +5
Accurate cell detection and classification are crucial for pathological analysis, directly affecting diagnostic accuracy and treatment planning. To capture complex cellular interac…
Path2ST: Hierarchical Cell-Tissue Grounded Cross-Modal Translation for Spatial Transcriptomics
Ruochen Liu, Wei Lou
Predicting spatial gene expression from hematoxylin and eosin (H\&E)-stained images offers a cost-effective alternative to spatial transcriptomics (ST). However, existing methods t…
Cell Graph Transformer for Nuclei Classification
Wei Lou, Guanbin Li, Xiang Wan +1
Nuclei classification is a critical step in computer-aided diagnosis with histopathology images. In the past, various methods have employed graph neural networks (GNN) to analyze c…
Multi-stream Cell Segmentation with Low-level Cues for Multi-modality Images
Wei Lou, Xinyi Yu, Chenyu Liu +4
Cell segmentation for multi-modal microscopy images remains a challenge due to the complex textures, patterns, and cell shapes in these images. To tackle the problem, we first deve…
Structure Embedded Nucleus Classification for Histopathology Images
Wei Lou, Xiang Wan, Guanbin Li +4
Nuclei classification provides valuable information for histopathology image analysis. However, the large variations in the appearance of different nuclei types cause difficulties…
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…