Lawrence Hamilton Staib — accepted AI-conference papers

2023

Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective

Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, David A. Clifton, S Kevin Zhou +2

NeurIPS 2023poster

For medical image segmentation, contrastive learning is the dominant practice to improve the quality of visual representations by contrasting semantically similar and dissimilar pairs of samples. This is enabled by the observation that without accessing ground truth labels, negative examples with tr…

Cited by 105 Source ↗PDF ↗code ↗Scholar ↗

2022

Class-Aware Adversarial Transformers for Medical Image Segmentation

Chenyu You, Ruihan Zhao, Fenglin Liu, Siyuan Dong, Sandeep P. Chinchali, ufuk topcu +2

NeurIPS 2022accept

Transformers have made remarkable progress towards modeling long-range dependencies within the medical image analysis domain. However, current transformer-based models suffer from several disadvantages: (1) existing methods fail to capture the important features of the images due to the naive tokeni…

Cited by 163 Source ↗PDF ↗Scholar ↗