4 papers
ZScribbleSeg: A comprehensive segmentation framework with modeling of efficient annotation and maximization of scribble supervision
Ke Zhang, Bomin Wang, Hangqi Zhou +1
Curating fully annotated datasets for medical image segmentation is labour-intensive and expertise-demanding. To alleviate this problem, prior studies have explored scribble annota…
Beyond Forgetting in Continual Medical Image Segmentation: A Comprehensive Benchmark Study
Bomin Wang, Hangqi Zhou, Yibo Gao +1
Continual learning (CL) is essential for deploying medical image segmentation models in clinical environments where imaging domains, anatomical targets, and diagnostic tasks evolve…
Learning Concept-Driven Logical Rules for Interpretable and Generalizable Medical Image Classification
Yibo Gao, Hangqi Zhou, Zheyao Gao +4
The pursuit of decision safety in clinical applications highlights the potential of concept-based methods in medical imaging. While these models offer active interpretability, they…
Empowering Medical Multi-Agents with Clinical Consultation Flow for Dynamic Diagnosis
Sihan Wang, Suiyang Jiang, Yibo Gao +3
Traditional AI-based healthcare systems often rely on single-modal data, limiting diagnostic accuracy due to incomplete information. However, recent advancements in foundation mode…