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EchoVLM: Measurement-Grounded Multimodal Learning for Echocardiography
Yuheng Li, Yue Zhang, Abdoul Aziz Amadou +5
Echocardiography is the most widely used imaging modality in cardiology, yet its interpretation remains labor-intensive and inherently multimodal, requiring view recognition, quant…
TIR-Bench: A Comprehensive Benchmark for Agentic Thinking-with-Images Reasoning
Ming Li, Jike Zhong, Shitian Zhao +6
The frontier of visual reasoning is shifting toward models like OpenAI o3, which can intelligently create and operate tools to transform images for problem-solving, also known as t…
Are Video Models Emerging as Zero-Shot Learners and Reasoners in Medical Imaging?
Yuxiang Lai, Jike Zhong, Ming Li +2
Recent advances in large generative models have shown that simple autoregressive formulations, when scaled appropriately, can exhibit strong zero-shot generalization across domains…
MedVista3D: Vision-Language Modeling for Reducing Diagnostic Errors in 3D CT Disease Detection, Understanding and Reporting
Yuheng Li, Yenho Chen, Yuxiang Lai +3
Radiologic diagnostic errors-under-reading errors, inattentional blindness, and communication failures-remain prevalent in clinical practice. These issues often stem from missed lo…
Patient-Specific Autoregressive Models for Organ Motion Prediction in Radiotherapy
Yuxiang Lai, Jike Zhong, Vanessa Su +1
Radiotherapy often involves a prolonged treatment period. During this time, patients may experience organ motion due to breathing and other physiological factors. Predicting and mo…
Think or Not Think: A Study of Explicit Thinking in Rule-Based Visual Reinforcement Fine-Tuning
Ming Li, Jike Zhong, Shitian Zhao +4
This paper investigates the role of explicit thinking process in rule-based reinforcement fine-tuning (RFT) for MLLMs. We first propose CLS-RL for MLLM image classification, using…
Med-R1: Reinforcement Learning for Generalizable Medical Reasoning in Vision-Language Models
Yuxiang Lai, Jike Zhong, Ming Li +4
Vision-language models (VLMs) have achieved impressive progress in natural image reasoning, yet their potential in medical imaging remains underexplored. Medical vision-language ta…