4 papers · 1 filter
MedVeriSeg: Teaching LISA-Like Medical Segmentation Models to Verify Query Validity Without Extra Training
Qinyue Tong, Xiaozhen Wang, Ziqian Lu +3
Despite recent progress in text-prompt-based medical image segmentation, existing LISA-like MLLM-based methods typically generate masks regardless of whether the target specified i…
Unlocking the Forgery Detection Potential of Vanilla MLLMs: A Novel Training-Free Pipeline
Rui Zuo, Qinyue Tong, Zhe-Ming Lu +1
With the rapid advancement of artificial intelligence-generated content (AIGC) technologies, including multimodal large language models (MLLMs) and diffusion models, image generati…
MediRound: Multi-Round Entity-Level Reasoning Segmentation in Medical Images
Qinyue Tong, Ziqian Lu, Jun Liu +3
Despite notable progress in text-guided medical image segmentation nowadays, these methods are limited to single-round dialogues and fail to support multi-round reasoning, which is…
MediSee: Reasoning-based Pixel-level Perception in Medical Images
Qinyue Tong, Ziqian Lu, Jun Liu +2
Despite remarkable advancements in pixel-level medical image perception, existing methods are either limited to specific tasks or heavily rely on accurate bounding boxes or text la…