13 papers
UniField++: A Unified Agentic Framework with Loop Reasoning for MRI Field-Strength Enhancement
Yiyang Lin, Chenhui Wang, Tianliang Yao +5
MRI field-strength enhancement seeks to combine the accessibility of low-field scanners with the image quality of high-field scanners. Yet, existing methods remain prone to anatomi…
Volumetric Radiology AI in the Era of Multimodal Large Language Models
Zanting Ye, Shengyuan Liu, Xin Liu +16
Advances in multimodal large language models (MLLMs) are extending radiological artificial intelligence (AI) beyond task-specific image analysis toward multimodal understanding and…
Towards Autonomous and Auditable Medical Imaging Model Development
Shengyuan Liu, Jia-Xuan Jiang, Boyun Zheng +8
Large language model (LLM) agents are beginning to automate machine learning engineering (MLE) by coupling planning, code execution, debugging, and empirical feedback. Translating…
AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery
Guiyao Tie, Jiawen Shi, Dingjie Song +20
Scientific research is being reshaped by AI systems that move beyond isolated assistance toward longer-horizon workflows spanning literature grounding, hypothesis generation, exper…
NeuroClaw Technical Report
Cheng Wang, Zhibin He, Zhihao Peng +7
Agentic artificial intelligence systems promise to accelerate scientific workflows, but neuroimaging poses unique challenges: heterogeneous modalities (sMRI, fMRI, dMRI, EEG), long…
Towards a Medical AI Scientist
Hongtao Wu, Boyun Zheng, Dingjie Song +5
Autonomous systems that generate scientific hypotheses, conduct experiments, and draft manuscripts have recently emerged as a promising paradigm for accelerating discovery. However…
Brain-WM: Brain Glioblastoma World Model
Chenhui Wang, Boyun Zheng, Liuxin Bao +4
Precise prognostic modeling of glioblastoma (GBM) under varying treatment interventions is essential for optimizing clinical outcomes. While generative AI has shown promise in simu…
UniField: A Unified Field-Aware MRI Enhancement Framework
Yiyang Lin, Chenhui Wang, Zhihao Peng +1
Magnetic Resonance Imaging (MRI) field-strength enhancement holds immense value for both clinical diagnostics and advanced research. However, existing methods typically focus on is…
Unveiling and Bridging the Functional Perception Gap in MLLMs: Atomic Visual Alignment and Hierarchical Evaluation via PET-Bench
Zanting Ye, Xiaolong Niu, Xuanbin Wu +14
While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in tasks such as abnormality detection and report generation for anatomical modalities, thei…
OmniBrainBench: A Comprehensive Multimodal Benchmark for Brain Imaging Analysis Across Multi-stage Clinical Tasks
Zhihao Peng, Cheng Wang, Shengyuan Liu +5
Brain imaging analysis is crucial for diagnosing and treating brain disorders, and multimodal large language models (MLLMs) are increasingly supporting it. However, current brain i…
Expertise-aware Multi-LLM Recruitment and Collaboration for Medical Decision-Making
Liuxin Bao, Zhihao Peng, Xiaofei Zhou +3
Medical Decision-Making (MDM) is a complex process requiring substantial domain-specific expertise to effectively synthesize heterogeneous and complicated clinical information. Whi…
MAC: Masked Agent Collaboration Boosts Large Language Model Medical Decision-Making
Zhihao Peng, Liuxin Bao, Yixuan Yuan
Large language models (LLMs) have proven effective in artificial intelligence, where the multi-agent system (MAS) holds considerable promise for healthcare development by achieving…
MAP: Evaluation and Multi-Agent Enhancement of Large Language Models for Inpatient Pathways
Zhen Chen, Zhihao Peng, Xusheng Liang +5
Inpatient pathways demand complex clinical decision-making based on comprehensive patient information, posing critical challenges for clinicians. Despite advancements in large lang…