23 citations · 28 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis
Yibo Gao, Zheyao Gao, Xin Gao +3
Due to the high stakes in medical decision-making, there is a compelling demand for interpretable deep learning methods in medical image analysis. Concept Bottleneck Models (CBM) h…
BayeSeg: Bayesian Modeling for Medical Image Segmentation with Interpretable Generalizability
Shangqi Gao, Hangqi Zhou, Yibo Gao +1
Due to the cross-domain distribution shift aroused from diverse medical imaging systems, many deep learning segmentation methods fail to perform well on unseen data, which limits t…