5 papers
Geometry-aware Prototype Learning for Cross-domain Few-shot Medical Image Segmentation
Feifan Song, Yuntian Bo, Haofeng Zhang
Cross-domain few-shot medical image segmentation (CD-FSMIS) requires a model to generalise simultaneously to novel anatomical categories and unseen imaging domains from only a hand…
Focus on Background: Exploring SAM's Potential in Few-shot Medical Image Segmentation with Background-centric Prompting
Yuntian Bo, Yazhou Zhu, Piotr Koniusz +1
Conventional few-shot medical image segmentation (FSMIS) approaches face performance bottlenecks that hinder broader clinical applicability. Although the Segment Anything Model (SA…
ReconDrive: Fast Feed-Forward 4D Gaussian Splatting for Autonomous Driving Scene Reconstruction
Haibao Yu, Kuntao Xiao, Jiahang Wang +7
High-fidelity visual reconstruction and novel-view synthesis are essential for realistic closed-loop evaluation in autonomous driving. While 4D Gaussian Splatting (4DGS) offers a p…
Contrastive Graph Modeling for Cross-Domain Few-Shot Medical Image Segmentation
Yuntian Bo, Tao Zhou, Zechao Li +2
Cross-domain few-shot medical image segmentation (CD-FSMIS) offers a promising and data-efficient solution for medical applications where annotations are severely scarce and multim…
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image Segmentation
Yuntian Bo, Yazhou Zhu, Lunbo Li +1
Existing few-shot medical image segmentation (FSMIS) models fail to address a practical issue in medical imaging: the domain shift caused by different imaging techniques, which lim…