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Self supervised learning for segmentation of kidney and kidney tumor on KiTS challenge data

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Self-supervised learning for Segmentation

This work proposes a self-supervised learning framework for kidney segmentation, leveraging anotomical asymmetry of kidneys as a novel proxy task.

Please see our paper Self-Supervised Learning for Segmentation for details.

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Self supervised learning for segmentation of kidney and kidney tumor on KiTS challenge data

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