8 papers
RAU: Reference-based Anatomical Understanding with Vision Language Models
Yiwei Li, Yikang Liu, Jiaqi Guo +7
Anatomical understanding through deep learning is critical for automatic report generation, intra-operative navigation, and organ localization in medical imaging; however, its prog…
Retrieval-augmented Few-shot Medical Image Segmentation with Foundation Models
Lin Zhao, Xiao Chen, Eric Z. Chen +3
Medical image segmentation is crucial for clinical decision-making, but the scarcity of annotated data presents significant challenges. Few-shot segmentation (FSS) methods show pro…
DiffDenoise: Self-Supervised Medical Image Denoising with Conditional Diffusion Models
Basar Demir, Yikang Liu, Xiao Chen +5
Many self-supervised denoising approaches have been proposed in recent years. However, these methods tend to overly smooth images, resulting in the loss of fine structures that are…
Leveraging Diffusion Model and Image Foundation Model for Improved Correspondence Matching in Coronary Angiography
Lin Zhao, Xin Yu, Yikang Liu +4
Accurate correspondence matching in coronary angiography images is crucial for reconstructing 3D coronary artery structures, which is essential for precise diagnosis and treatment…
Adapting Vision Foundation Models for Real-time Ultrasound Image Segmentation
Xiaoran Zhang, Eric Z. Chen, Lin Zhao +6
We propose a novel approach that adapts hierarchical vision foundation models for real-time ultrasound image segmentation. Existing ultrasound segmentation methods often struggle w…
LSU-Net: Lightweight Automatic Organs Segmentation Network For Medical Images
Yujie Ding, Shenghua Teng, Zuoyong Li +1
UNet and its variants have widespread applications in medical image segmentation. However, the substantial number of parameters and computational complexity of these models make th…