7 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…
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…
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…
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,…
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation
Yihang Fu, Ziyang Chen, Yiwen Ye +3
Medical images often exhibit distribution shifts due to variations in imaging protocols and scanners across different medical centers. Domain Generalization (DG) methods aim to tra…
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…
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…