A feature-augmentation framework with a learned channel selector and covariance-guided intensity sampler that reports the best average domain-generalized segmentation on Prostate and Fundus benchmarks.
Unetr: Transformers for 3d medical image segmentation,
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Learning Semantic Directions for Feature Augmentation in Domain-Generalized Medical Segmentation
A feature-augmentation framework with a learned channel selector and covariance-guided intensity sampler that reports the best average domain-generalized segmentation on Prostate and Fundus benchmarks.