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Table 4 Quantitative comparisons on cremi_triplet and mouse_triplet

From: Sparse self-attention aggregation networks for neural sequence slice interpolation

Methods cremi_triplet A cremi_triplet B cremi_triplet C mouse_triplet
  PSNR SSIM PSNR SSIM PSNR SSIM IE PSNR SSIM IE
SepConv-L s [9] 17.52 0.4095 16.32 0.3522 16.07 0.3454 29.82 12.56 0.1573 48.03
DAIN-L s [12] 16.78 0.4264 15.67 0.3460 15.24 0.3210 33.59 13.06 0.1973 44.26
SSAN(Ours) 18.26 0.4374 16.79 0.3712 16.46 0.3575 28.38 15.04 0.2156 34.81
  1. The proposed SSAN algorithm significantly surpasses other methods in terms of PSNR, SSIM and IE
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