151 citations · 205 across the 8 of their papers we have counts for
9 papers
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…
Auditable agentic AI for evidence-grounded thyroid ultrasound diagnosis and reporting
Haifan Gong, Shiyu Chen, Bodong Wang +11
Thyroid ultrasound diagnosis requires coordinated lesion localization, measurement, risk stratification and reporting, yet most AI systems address these tasks in isolation and prov…
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…
Diffusion-based Data Augmentation for Nuclei Image Segmentation
Xinyi Yu, Guanbin Li, Wei Lou +4
Nuclei segmentation is a fundamental but challenging task in the quantitative analysis of histopathology images. Although fully-supervised deep learning-based methods have made sig…
The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions
Jun Ma, Ronald Xie, Shamini Ayyadhury +37
Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or req…
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…