1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
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…
eess.IV2024
Intensity Confusion Matters: An Intensity-Distance Guided Loss for Bronchus Segmentation
Haifan Gong, Wenhao Huang, Huan Zhang +5
Automatic segmentation of the bronchial tree from CT imaging is important, as it provides structural information for disease diagnosis. Despite the merits of previous automatic bro…
cs.CV2024★ 1 cited
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…