923 citations · 1.2k across the 30 of their papers we have counts for
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Diffuse-UDA: Addressing Unsupervised Domain Adaptation in Medical Image Segmentation with Appearance and Structure Aligned Diffusion Models
Haifan Gong, Yitao Wang, Yihan Wang +3
The scarcity and complexity of voxel-level annotations in 3D medical imaging present significant challenges, particularly due to the domain gap between labeled datasets from well-r…
Self-Supervised Alignment Learning for Medical Image Segmentation
Haofeng Li, Yiming Ouyang, Xiang Wan
Recently, self-supervised learning (SSL) methods have been used in pre-training the segmentation models for 2D and 3D medical images. Most of these methods are based on reconstruct…
nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model
Haifan Gong, Luoyao Kang, Yitao Wang +2
In the field of biomedical image analysis, the quest for architectures capable of effectively capturing long-range dependencies is paramount, especially when dealing with 3D image…
Cell Graph Transformer for Nuclei Classification
Wei Lou, Guanbin Li, Xiang Wan +1
Nuclei classification is a critical step in computer-aided diagnosis with histopathology images. In the past, various methods have employed graph neural networks (GNN) to analyze c…
UniCell: Universal Cell Nucleus Classification via Prompt Learning
Junjia Huang, Haofeng Li, Xiang Wan +1
The recognition of multi-class cell nuclei can significantly facilitate the process of histopathological diagnosis. Numerous pathological datasets are currently available, but thei…