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cs.CV2025
MedReasoner: Reinforcement Learning Drives Reasoning Grounding from Clinical Thought to Pixel-Level Precision
Zhonghao Yan, Muxi Diao, Yuxuan Yang +7
Accurately grounding regions of interest (ROIs) is critical for diagnosis and treatment planning in medical imaging. While multimodal large language models (MLLMs) combine visual p…
cs.CV2025
Trade-offs in Image Generation: How Do Different Dimensions Interact?
Sicheng Zhang, Binzhu Xie, Zhonghao Yan +7
Model performance in text-to-image (T2I) and image-to-image (I2I) generation often depends on multiple aspects, including quality, alignment, diversity, and robustness. However, mo…
cs.CV2025
PGP-SAM: Prototype-Guided Prompt Learning for Efficient Few-Shot Medical Image Segmentation
Zhonghao Yan, Zijin Yin, Tianyu Lin +3
The Segment Anything Model (SAM) has demonstrated strong and versatile segmentation capabilities, along with intuitive prompt-based interactions. However, customizing SAM for medic…