5 citations · 8 across the 21 of their papers we have counts for
7 papers · 1 filter
START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation
Jintao Guo, Lei Qi, Yinghuan Shi +1
Domain Generalization (DG) aims to enable models to generalize to unseen target domains by learning from multiple source domains. Existing DG methods primarily rely on convolutiona…
The Devil is in the Statistics: Mitigating and Exploiting Statistics Difference for Generalizable Semi-supervised Medical Image Segmentation
Muyang Qiu, Jian Zhang, Lei Qi +3
Despite the recent success of domain generalization in medical image segmentation, voxel-wise annotation for all source domains remains a huge burden. Semi-supervised domain genera…
Learn to Preserve and Diversify: Parameter-Efficient Group with Orthogonal Regularization for Domain Generalization
Jiajun Hu, Jian Zhang, Lei Qi +2
Domain generalization (DG) aims to avoid the performance degradation of the model when the distribution shift between the limited training data and unseen test data occurs. Recentl…
Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image Segmentation
Qinghe Ma, Jian Zhang, Lei Qi +3
Both limited annotation and domain shift are prevalent challenges in medical image segmentation. Traditional semi-supervised segmentation and unsupervised domain adaptation methods…
SETA: Semantic-Aware Token Augmentation for Domain Generalization
Jintao Guo, Lei Qi, Yinghuan Shi +1
Domain generalization (DG) aims to enhance the model robustness against domain shifts without accessing target domains. A prevalent category of methods for DG is data augmentation,…
Stitching, Fine-tuning, Re-training: A SAM-enabled Framework for Semi-supervised 3D Medical Image Segmentation
Shumeng Li, Lei Qi, Qian Yu +3
Segment Anything Model (SAM) fine-tuning has shown remarkable performance in medical image segmentation in a fully supervised manner, but requires precise annotations. To reduce th…
Learning Generalizable Models via Disentangling Spurious and Enhancing Potential Correlations
Na Wang, Lei Qi, Jintao Guo +2
Domain generalization (DG) intends to train a model on multiple source domains to ensure that it can generalize well to an arbitrary unseen target domain. The acquisition of domain…