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20112026
most citedToward Early-Warning Detection of Gravitational Waves from Compact Binary Coalescence

257 citations · 284 across the 15 of their papers we have counts for

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12 papers · 1 filter

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

AGE-MIL: Anchor-Guided Evidence Learning for Patient-Level Prediction

Jiawei Niu, Jian Chen, Di Zhang +8

Existing computational pathology methods predominantly operate within whole-slide image (WSI)-level multiple instance learning (MIL) paradigms, while patient-level modeling remains…

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

Vision Transformers for Preoperative CT-Based Prediction of Histopathologic Chemotherapy Response Score in High-Grade Serous Ovarian Carcinoma

Francesca Fati, Felipe Coutinho, Marika Reinius +25

Purpose. High-grade serous ovarian carcinoma (HGSOC) is characterized by pronounced biological and spatial heterogeneity and is frequently diagnosed at an advanced stage. Neoadjuva…

cs.CV2026

CARE: A Molecular-Guided Foundation Model with Adaptive Region Modeling for Whole Slide Image Analysis

Di Zhang, Zhangpeng Gong, Xiaobo Pang +14

Foundation models have recently achieved impressive success in computational pathology, demonstrating strong generalization across diverse histopathology tasks. However, existing m…

cs.CV2026★ 1 cited

Developing Predictive and Robust Radiomics Models for Chemotherapy Response in High-Grade Serous Ovarian Carcinoma

Sepideh Hatamikia, Geevarghese George, Florian Schwarzhans +10

Objectives: High-grade serous ovarian carcinoma (HGSOC) is typically diagnosed at an advanced stage with extensive peritoneal metastases, making treatment challenging. Neoadjuvant…

cs.CV2025

RSeg: Training-Free OOD Medical Tumor Segmentation via Anatomical Reasoning and Statistical Rejection

Shuaike Shen, Ke Liu, Jiaqing Xie +5

Foundation models for medical image segmentation struggle under out-of-distribution (OOD) shifts, often producing fragmented false positives on OOD tumors. We introduce RSeg,…

cs.CV2025

Integrating Pathology and CT Imaging for Personalized Recurrence Risk Prediction in Renal Cancer

Daniël Boeke, Cedrik Blommestijn, Rebecca N. Wray +8

Recurrence risk estimation in clear cell renal cell carcinoma (ccRCC) is essential for guiding postoperative surveillance and treatment. The Leibovich score remains widely used for…

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

CTARR: A fast and robust method for identifying anatomical regions on CT images via atlas registration

Thomas Buddenkotte, Roland Opfer, Julia Krüger +2

Medical image analysis tasks often focus on regions or structures located in a particular location within the patient's body. Often large parts of the image may not be of interest…