An equivariant U-Net using symmetric rotation-equivariant kernels improves retinal vessel segmentation on rotated images while using far fewer parameters than baseline networks.
Experimental Setup Dataset: We evaluate using the public retina vessel DRIVE dataset [19], which consists of 40 2D RGB fundus images with paired binary vessel segmentation labels
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Improved Vessel Segmentation with Symmetric Rotation-Equivariant U-Net
An equivariant U-Net using symmetric rotation-equivariant kernels improves retinal vessel segmentation on rotated images while using far fewer parameters than baseline networks.