11 papers
Benchmarking Pathology Foundation Models for Spatial Domain Understanding
Bokai Zhao, Yiyang Zhang, Yuanchi Zhu +6
Pathology foundation models (PFMs) have emerged as a core approach for learning transferable representations from whole slide images (WSIs), and they are typically benchmarked thro…
MedVR: Annotation-Free Medical Visual Reasoning via Agentic Reinforcement Learning
Zheng Jiang, Heng Guo, Chengyu Fang +4
Medical Vision-Language Models (VLMs) hold immense promise for complex clinical tasks, but their reasoning capabilities are often constrained by text-only paradigms that fail to gr…
MUSE: Multi-Scale Dense Self-Distillation for Nucleus Detection and Classification
Zijiang Yang, Hanqing Chao, Bokai Zhao +10
Nucleus detection and classification (NDC) in histopathology analysis is a fundamental task that underpins a wide range of high-level pathology applications. However, existing meth…
A Deep Learning System for Rapid and Accurate Warning of Acute Aortic Syndrome on Non-contrast CT in China
Yujian Hu, Yilang Xiang, Yan-Jie Zhou +41
The accurate and timely diagnosis of acute aortic syndromes (AAS) in patients presenting with acute chest pain remains a clinical challenge. Aortic CT angiography (CTA) is the imag…
M3Ret: Unleashing Zero-shot Multimodal Medical Image Retrieval via Self-Supervision
Che Liu, Zheng Jiang, Chengyu Fang +5
Medical image retrieval is essential for clinical decision-making and translational research, relying on discriminative visual representations. Yet, current methods remain fragment…
Anatomy-Aware Low-Dose CT Denoising via Pretrained Vision Models and Semantic-Guided Contrastive Learning
Runze Wang, Zeli Chen, Zhiyun Song +8
To reduce radiation exposure and improve the diagnostic efficacy of low-dose computed tomography (LDCT), numerous deep learning-based denoising methods have been developed to mitig…