76 citations · 233 across the 46 of their papers we have counts for
7 papers · 1 filter
Masked Autoencoders are Parameter-Efficient Federated Continual Learners
Yuchen He, Xiangfeng Wang
Federated learning is a specific distributed learning paradigm in which a central server aggregates updates from multiple clients' local models, thereby enabling the server to lear…
Interactive 3D Medical Image Segmentation with SAM 2
Chuyun Shen, Wenhao Li, Yuhang Shi +1
Interactive medical image segmentation (IMIS) has shown significant potential in enhancing segmentation accuracy by integrating iterative feedback from medical professionals. Howev…
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation
Chuyun Shen, Wenhao Li, Haoqing Chen +5
Radiologists must utilize multiple modal images for tumor segmentation and diagnosis due to the limitations of medical imaging and the diversity of tumor signals. This leads to the…
Temporally-Extended Prompts Optimization for SAM in Interactive Medical Image Segmentation
Chuyun Shen, Wenhao Li, Ya Zhang +1
The Segmentation Anything Model (SAM) has recently emerged as a foundation model for addressing image segmentation. Owing to the intrinsic complexity of medical images and the high…
Boundary-aware Supervoxel-level Iteratively Refined Interactive 3D Image Segmentation with Multi-agent Reinforcement Learning
Chaofan Ma, Qisen Xu, Xiangfeng Wang +4
Interactive segmentation has recently been explored to effectively and efficiently harvest high-quality segmentation masks by iteratively incorporating user hints. While iterative…
Interactive Medical Image Segmentation with Self-Adaptive Confidence Calibration
Wenhao Li, Qisen Xu, Chuyun Shen +5
Medical image segmentation is one of the fundamental problems for artificial intelligence-based clinical decision systems. Current automatic medical image segmentation methods are…
Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning
Xuan Liao, Wenhao Li, Qisen Xu +5
Existing automatic 3D image segmentation methods usually fail to meet the clinic use. Many studies have explored an interactive strategy to improve the image segmentation performan…