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Found 2 papers, 1 papers with code
Contrastive and Selective Hidden Embeddings for Medical Image Segmentation
Medical image segmentation has been widely recognized as a pivot procedure for clinical diagnosis, analysis, and treatment planning.
Self-Ensembling Contrastive Learning for Semi-Supervised Medical Image Segmentation
In this paper, we aim to boost the performance of semi-supervised learning for medical image segmentation with limited labels using a self-ensembling contrastive learning technique.
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