76 citations · 85 across the 6 of their papers we have counts for
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HUR-MACL: High-Uncertainty Region-Guided Multi-Architecture Collaborative Learning for Head and Neck Multi-Organ Segmentation
Xiaoyu Liu, Siwen Wei, Linhao Qu +4
Accurate segmentation of organs at risk in the head and neck is essential for radiation therapy, yet deep learning models often fail on small, complexly shaped organs. While hybrid…
ME-Mamba: Multi-Expert Mamba with Efficient Knowledge Capture and Fusion for Multimodal Survival Analysis
Chengsheng Zhang, Linhao Qu, Xiaoyu Liu +1
Survival analysis using whole-slide images (WSIs) is crucial in cancer research. Despite significant successes, pathology images typically only provide slide-level labels, which hi…
Deep Mutual Learning among Partially Labeled Datasets for Multi-Organ Segmentation
Xiaoyu Liu, Linhao Qu, Ziyue Xie +2
The task of labeling multiple organs for segmentation is a complex and time-consuming process, resulting in a scarcity of comprehensively labeled multi-organ datasets while the eme…
Towards Label-efficient Automatic Diagnosis and Analysis: A Comprehensive Survey of Advanced Deep Learning-based Weakly-supervised, Semi-supervised and Self-supervised Techniques in Histopathological Image Analysis
Linhao Qu, Siyu Liu, Xiaoyu Liu +2
Histopathological images contain abundant phenotypic information and pathological patterns, which are the gold standards for disease diagnosis and essential for the prediction of p…