17 papers
ASAP: Advancing Medical Volumetric Representation Learning with Anatomy-aware Semantically-adaptive Pre-training
Rongsheng Wang, Fenghe Tang, Zihang Jiang +10
Learning transferable and interpretable representations from medical volumetric scans remains challenging due to complex anatomical structures and weak, heterogeneous supervision p…
MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM
Wenliang Li, Rui Yan, Xu Zhang +10
Large language models (LLMs) have demonstrated notable potential in medical applications, yet they face substantial challenges in handling complex real-world clinical diagnoses usi…
Med3D-R1: Incentivizing Clinical Reasoning in 3D Medical Vision-Language Models for Abnormality Diagnosis
Haoran Lai, Zihang Jiang, Kun Zhang +6
Developing 3D vision-language models with robust clinical reasoning remains a challenge due to the inherent complexity of volumetric medical imaging, the tendency of models to over…
Histomorphology-Guided Prototypical Multi-Instance Learning for Breast Cancer WSI Classification
Baizhi Wang, Rui Yan, Wenxin Ma +6
Histomorphology is crucial in cancer diagnosis. However, existing whole slide image (WSI) classification methods struggle to effectively incorporate histomorphology information, li…
Equivariant Sampling for Improving Diffusion Model-based Image Restoration
Chenxu Wu, Qingpeng Kong, Peiang Zhao +5
Recent advances in generative models, especially diffusion models, have significantly improved image restoration (IR) performance. However, existing problem-agnostic diffusion mode…
Bridged Semantic Alignment for Zero-shot 3D Medical Image Diagnosis
Haoran Lai, Zihang Jiang, Qingsong Yao +6
3D medical images such as computed tomography are widely used in clinical practice, offering a great potential for automatic diagnosis. Supervised learning-based approaches have ac…