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SSL-Unet: A Self-Supervised Learning Strategy Base on U-Net for Retinal Vessel Segmentation

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posted on 2021-10-19, 04:08 authored by Chao MaChao Ma
We propose a SSL-Unet model for retinal vascular segmentation as well as two self-supervised training strategies. The strategy can help the self-supervised module to learn pseudo labels for improving the segmentation performance. Moreover, the fusion of both self-supervised and supervised paradigms is applied to retinal segmentation for the first time. Meanwhile, it can also be extended to any segmentation network.

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Email Address of Submitting Author

macsy@cqnu.edu.cn

Submitting Author's Institution

CQNU

Submitting Author's Country

  • China

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