1 citations · 2 across the 10 of their papers we have counts for
10 papers
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…
Claw-Eval-Live: A Live Agent Benchmark for Evolving Real-World Workflows
Chenxin Li, Zhengyang Tang, Mingxin Huang +8
LLM agents are expected to complete end-to-end units of work across software tools, business services, and local workspaces. Yet many agent benchmarks freeze a curated task set at…
Topology-Guided Biomechanical Profiling: A White-Box Framework for Opportunistic Screening of Spinal Instability on Routine CT
Zanting Ye, Xuanbin Wu, Guoqing Zhong +9
Routine oncologic computed tomography (CT) presents an ideal opportunity for screening spinal instability, yet prophylactic stabilization windows are frequently missed due to the c…
MedPruner: Training-Free Hierarchical Token Pruning for Efficient 3D Medical Image Understanding in Vision-Language Models
Shengyuan Liu, Zanting Ye, Yunrui Lin +6
While specialized Medical Vision-Language Models (VLMs) have achieved remarkable success in interpreting 2D and 3D medical modalities, their deployment for 3D volumetric data remai…
MedSAM-Agent: Empowering Interactive Medical Image Segmentation with Multi-turn Agentic Reinforcement Learning
Shengyuan Liu, Liuxin Bao, Qi Yang +6
Medical image segmentation is evolving from task-specific models toward generalizable frameworks. Recent research leverages Multi-modal Large Language Models (MLLMs) as autonomous…
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…
Medical Reasoning in the Era of LLMs: A Systematic Review of Enhancement Techniques and Applications
Zizhan Ma, Wenxuan Wang, Meidan Ding +7
The proliferation of Large Language Models (LLMs) in medicine has enabled impressive capabilities, yet a critical gap remains in their ability to perform systematic, transparent, a…
TumorGen: Boundary-Aware Tumor-Mask Synthesis with Rectified Flow Matching
Shengyuan Liu, Wenting Chen, Boyun Zheng +3
Tumor data synthesis offers a promising solution to the shortage of annotated medical datasets. However, current approaches either limit tumor diversity by using predefined masks o…