45 citations · 69 across the 10 of their papers we have counts for
4 papers · 1 filter
KHiM-Mamba: Injecting Pathology Knowledge into Mamba via Hidden-State Modulation for Whole Slide Image Analysis
Qixiang Zhang, Yi Li, Tianqi Xiang +4
Whole slide image analysis is commonly formulated as multiple instance learning (MIL), where instance features are contextually updated and aggregated into a slide representation,…
Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation
Haonan Wang, Peng Cao, Xiaoli Liu +2
Most state-of-the-art methods for medical image segmentation adopt the encoder-decoder architecture. However, this U-shaped framework still has limitations in capturing the non-loc…
Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
Haonan Wang, Xiaomeng Li
Volume-wise labeling in 3D medical images is a time-consuming task that requires expertise. As a result, there is growing interest in using semi-supervised learning (SSL) technique…
DHC: Dual-debiased Heterogeneous Co-training Framework for Class-imbalanced Semi-supervised Medical Image Segmentation
Haonan Wang, Xiaomeng Li
The volume-wise labeling of 3D medical images is expertise-demanded and time-consuming; hence semi-supervised learning (SSL) is highly desirable for training with limited labeled d…