4 papers
STNAGNN: Data-driven Spatio-temporal Brain Connectivity beyond FC
Jiyao Wang, Nicha C. Dvornek, Peiyu Duan +3
In recent years, graph neural networks (GNNs) have been widely applied in the analysis of brain fMRI, yet defining the connectivity between ROIs remains a challenge in noisy fMRI d…
Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations
Chenyu You, Yifei Min, Weicheng Dai +3
Fine-tuning pre-trained vision-language models, like CLIP, has yielded success on diverse downstream tasks. However, several pain points persist for this paradigm: (i) directly tun…
Mine yOur owN Anatomy: Revisiting Medical Image Segmentation with Extremely Limited Labels
Chenyu You, Weicheng Dai, Fenglin Liu +6
Recent studies on contrastive learning have achieved remarkable performance solely by leveraging few labels in the context of medical image segmentation. Existing methods mainly fo…
Adaptive Correspondence Scoring for Unsupervised Medical Image Registration
Xiaoran Zhang, John C. Stendahl, Lawrence Staib +3
We propose an adaptive training scheme for unsupervised medical image registration. Existing methods rely on image reconstruction as the primary supervision signal. However, nuisan…