4 citations · 11 across the 15 of their papers we have counts for
5 papers · 1 filter
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…
PathAgent: Toward Interpretable Analysis of Whole-slide Pathology Images via Large Language Model-based Agentic Reasoning
Jingyun Chen, Linghan Cai, Zhikang Wang +5
Analyzing whole-slide images (WSIs) requires an iterative, evidence-driven reasoning process that parallels how pathologists dynamically zoom, refocus, and self-correct while colle…
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…
Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation
Jinpeng Lu, Linghan Cai, Yinda Chen +4
Lightweight 3D medical image segmentation remains constrained by a fundamental \textit{``efficiency / robustness conflict''}, particularly when processing complex anatomical struct…
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…