activity
20242026
collaborators

10 papers

cs.CV2026

PlanPath: Exploration-Guided Orchestration for Patient-Level Pathology Reasoning

Jiusong Ge, Mingzhao He, Qidong Liu +8

A patient's pathology case spans tens of slides from distinct specimens and anatomical sites, each carrying non-redundant, site-specific evidence. Forming a patient-level conclusio…

cs.CV2026

Modeling Whole-Slide Images as Dynamic Tumor Microenvironment Fields

Lei Wu, Jiashuai Liu, Di Zhang +9

Due to the gigapixel-scale nature of whole-slide images (WSIs), weakly supervised WSI analysis is commonly formulated as a multiple instance learning (MIL) problem, where patch-lev…

cs.CV2026

Can Protein-Derived Knowledge Improve Pathology Foundation Models?

Di Zhang, Zhangpeng Gong, Jiashuai Liu +10

Molecularly guided pathology foundation models (PFMs) exploit transcriptomic or proteomic information to enrich whole-slide image (WSI) representations, yet effectively leveraging…

cs.CV2026

From Patches to Evidence Balls: Class-Conditioned Evidence Retrieval for Few-Shot Whole Slide Image Classification

Di Zhang, Li Zhang, Jiashuai Liu +9

Whole slide image (WSI) classification is an evidence-driven task, where diagnostic cues are often sparse, spatially organized, and class-dependent. Existing MIL and vision-languag…

cs.CV2026

PathNavigate: A Training-Free Pathology Agent with Surprise-Guided Scan and Shared Slide Memory for Whole-Slide Image VQA

Chunze Yang, Qidong Liu, Wenjie Zhao +10

Whole-slide image visual question answering (WSI-VQA) frames pathology as an extreme-context search problem: to answer a free-form clinical query, a system must first navigate a gi…

cs.CV2026

Thinking in Scales: Accelerating Gigapixel Pathology Image Analysis via Adaptive Continuous Reasoning

Jiusong Ge, Yingkang Zhan, Wenjie Zhao +13

Traditional whole slide image (WSI) analysis methods typically rely on the multiple instance learning (MIL) paradigm, which extracts patch-level features at high magnification and…

cs.CV2026

HAAF: Hierarchical Adaptation and Alignment of Foundation Models for Few-Shot Pathology Anomaly Detection

Chunze Yang, Wenjie Zhao, Yue Tang +5

Precision pathology relies on detecting fine-grained morphological abnormalities within specific Regions of Interest (ROIs), as these local, texture-rich cues - rather than global…

cs.CV2025

The Butterfly Effect in Pathology: Exploring Security in Pathology Foundation Models

Jiashuai Liu, Yingjia Shang, Yingkang Zhan +7

With the widespread adoption of pathology foundation models in both research and clinical decision support systems, exploring their security has become a critical concern. However,…

cs.CV2025

PH2ST:ST-Prompt Guided Histological Hypergraph Learning for Spatial Gene Expression Prediction

Yi Niu, Jiashuai Liu, Yingkang Zhan +8

Spatial Transcriptomics (ST) reveals the spatial distribution of gene expression in tissues, offering critical insights into biological processes and disease mechanisms. However, t…

cs.CV2024

A Self-Supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer

Inês P. Machado, Anna Reithmeir, Fryderyk Kogl +13

High-grade serous ovarian carcinoma (HGSOC) is characterised by significant spatial and temporal heterogeneity, typically manifesting at an advanced metastatic stage. A major chall…