10 papers
InViC: Intent-aware Visual Cues for Medical Visual Question Answering
Zhisong Wang, Ziyang Chen, Zanting Ye +3
Medical visual question answering (Med-VQA) aims to answer clinically relevant questions grounded in medical images. However, existing multimodal large language models (MLLMs) ofte…
Unified Start, Personalized End: Progressive Pruning for Efficient 3D Medical Image Segmentation
Linhao Li, Yiwen Ye, Ziyang Chen +1
3D medical image segmentation often faces heavy resource and time consumption, limiting its scalability and rapid deployment in clinical environments. Existing efficient segmentati…
MedSeqFT: Sequential Fine-tuning Foundation Models for 3D Medical Image Segmentation
Yiwen Ye, Yicheng Wu, Xiangde Luo +5
Foundation models have become a promising paradigm for advancing medical image analysis, particularly for segmentation tasks where downstream applications often emerge sequentially…
From Few to More: Scribble-based Medical Image Segmentation via Masked Context Modeling and Continuous Pseudo Labels
Zhisong Wang, Yiwen Ye, Ziyang Chen +3
Scribble-based weakly supervised segmentation methods have shown promising results in medical image segmentation, significantly reducing annotation costs. However, existing approac…
Pre-training Everywhere: Parameter-Efficient Fine-Tuning for Medical Image Analysis via Target Parameter Pre-training
Xingliang Lei, Yiwen Ye, Zhisong Wang +5
Parameter-efficient fine-tuning (PEFT) techniques have emerged to address overfitting and high computational costs associated with fully fine-tuning in self-supervised learning. Ma…
Enjoying Information Dividend: Gaze Track-based Medical Weakly Supervised Segmentation
Zhisong Wang, Yiwen Ye, Ziyang Chen +1
Weakly supervised semantic segmentation (WSSS) in medical imaging struggles with effectively using sparse annotations. One promising direction for WSSS leverages gaze annotations,…