1 citations · 1 across the 2 of their papers we have counts for
6 papers
PathFLIP: Fine-grained Language-Image Pretraining for Versatile Computational Pathology
Fengchun Liu, Songhan Jiang, Linghan Cai +2
While Vision-Language Models (VLMs) have achieved notable progress in computational pathology (CPath), the gigapixel scale and spatial heterogeneity of Whole Slide Images (WSIs) co…
PathReasoner-R1: Instilling Structured Reasoning into Pathology Vision-Language Model via Knowledge-Guided Policy Optimization
Songhan Jiang, Fengchun Liu, Ziyue Wang +2
Vision-Language Models (VLMs) are advancing computational pathology with superior visual understanding capabilities. However, current systems often reduce diagnosis to directly out…
IPGPhormer: Interpretable Pathology Graph-Transformer for Survival Analysis
Guo Tang, Songhan Jiang, Jinpeng Lu +2
Pathological images play an essential role in cancer prognosis, while survival analysis, which integrates computational techniques, can predict critical clinical events such as pat…
Prototype-Guided Cross-Modal Knowledge Enhancement for Adaptive Survival Prediction
Fengchun Liu, Linghan Cai, Zhikang Wang +4
Histo-genomic multimodal survival prediction has garnered growing attention for its remarkable model performance and potential contributions to precision medicine. However, a signi…
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…