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Found 2 papers, 2 papers with code
Semi-supervised Task-driven Data Augmentation for Medical Image Segmentation
In this work, we propose a novel task-driven data augmentation method for learning with limited labeled data where the synthetic data generator, is optimized for the segmentation task.
Semi-Supervised and Task-Driven Data Augmentation
However, there is potential to improve the approach by (i) explicitly modeling deformation fields (non-affine spatial transformation) and intensity transformations and (ii) leveraging unlabelled data during the generative process.
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