7 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…