collaborators

6 papers

cs.CV2026

Agentic Visual Reasoning in Whole-Slide Pathology Images via Active Perception

Jingyun Chen, Fengchun Liu, Linghan Cai +5

Whole-slide visual reasoning requires identifying sparse diagnostic evidence in gigapixel pathology slides and integrating observations across spatial scales. Existing WSI methods…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…