10 papers
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…
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…
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…
Towards a general-purpose foundation model for fMRI analysis
Cheng Wang, Yu Jiang, Zhihao Peng +18
Functional MRI (fMRI) is crucial for studying brain function and diagnosing neurological disorders. However, existing analysis methods suffer from reproducibility and transferabili…
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…
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…