23 citations · 27 across the 5 of their papers we have counts for
6 papers
Engram Neuron Inspired Adaptive Memorization for Lifelong Learning
Suiyang Jiang, Bomin Wang, Hangqi Zhou +2
Lifelong learning enables artificial systems to adapt to changing environments. To achieve this, an effective artificial learner should dynamically reorganize past and new experien…
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…
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
Kelly Payette, Céline Steger, Roxane Licandro +64
Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and th…
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…