Table 1 Comparison with existing methods on dataset 1.

From: MAN-GAN: a mask-adaptive normalization based generative adversarial networks for liver multi-phase CT image generation

Methods

Mode conversion

P to AP

P to PVP

P to DP

PSNR

SSIM

PSNR

SSIM

PSNR

SSIM

Non-contrast CT Images

26.02 ± 2.72

0.74 ± 0.07

24.73 ± 2.81

0.73 ± 0.07

24.84 ± 3.28

0.73 ± 0.08

pix2pix10

26.41 ± 2.63

0.78 ± 0.06

25.57 ± 2.77

0.77 ± 0.06

25.01 ± 3.11

0.76 ± 0.07

CycleGAN13

26.81 ± 2.73

0.79 ± 0.06

25.88 ± 2.98

0.78 ± 0.07

25.57 ± 3.44

0.77 ± 0.07

CUT12

26.58 ± 2.68

0.79 ± 0.06

24.51 ± 2.31

0.75 ± 0.06

24.90 ± 3.03

0.75 ± 0.07

F-LSeSim11

25.54 ± 2.29

0.78 ± 0.06

25.59 ± 2.72

0.77 ± 0.06

25.44 ± 3.25

0.77 ± 0.07

DINO9

26.88 ± 2.79

0.79 ± 0.06

25.21 ± 3.24

0.76 ± 0.06

24.96 ± 3.27

0.75 ± 0.07

CHAN8

26.67 ± 2.75

0.79 ± 0.06

25.67 ± 2.80

0.78 ± 0.06

25.14 ± 3.25

0.77 ± 0.07

Sun et al.21

26.48 ± 2.50

0.78 ± 0.06

25.52 ± 2.72

0.77 ± 0.06

25.05 ± 3.13

0.76 ± 0.07

Chen et al.22

27.45 ± 2.43

0.81 ± 0.03

26.49 ± 3.20

0.80 ± 0.06

25.86 ± 3.50

0.79 ± 0.07

MAN-GAN

27.71 ± 2.96

0.82 ± 0.06

26.76 ± 3.10

0.80 ± 0.06

26.17 ± 3.62

0.79 ± 0.07

  1. Significant values are in bold.
  2. Values were presented as mean ± SD.
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