Search Results for author:
Found 2 papers, 1 papers with code
TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation
Medical image segmentation - the prerequisite of numerous clinical needs - has been significantly prospered by recent advances in convolutional neural networks (CNNs).
Ranked #10 on
Medical Image Segmentation
on ETIS-LARIBPOLYPDB
Improve Model Generalization and Robustness to Dataset Bias with Bias-regularized Learning and Domain-guided Augmentation
In this study, we investigated model robustness to dataset bias using three large-scale Chest X-ray datasets: first, we assessed the dataset bias using vanilla training baseline; second, we proposed a novel multi-source domain generalization model by (a) designing a new bias-regularized loss function; and (b) synthesizing new data for domain augmentation.
