Table 4. Comparison of SNR value of background tissue between reconstructed images and real images using 17%PET images as input.

Group	Liver	Lung	Aorta	Lumbar spine
3D Unet-30s	11.29 (10.11, 12.95)*	7.40 (5.00, 9.01)*	13.85 (9.15, 17.47)*	7.19 (5.34, 11.07)*
P2P-30s	11.32 (9.46, 14.59)*	5.88 (4.43, 7.75)*	13.31 (10.05, 15.87)*	8.55 (6.78, 10.74)*
17%PET	4.70 (3.49, 5.19)	2.64 (2.03, 3.17)	3.93 (2.84, 5.30)	3.15 (2.05, 3.81)
s-PET	8.29 (7.77, 10.02)	5.00 (4.23, 5.64)	7.95 (6.22, 9.32)	5.95 (4.77, 8.28)
H	31.06	27.54	35.80	27.63
P	<0.0001	<0.0001	<0.0001	<0.0001

The italic font represents a statistical difference between this value and that of the 17%PET group. And * indicates that the value is statistically significant compared with the s-PET group. SNR, signal-to-noise ratio; PET, positron emission tomography; s-PET, standard positron emission tomography (per bed time: 90 s); 3D Unet, a deep network model based on CNN; P2P, Pixel2Pixel deep network model based on GAN; H, H value for the Kruskal-Wallis method; CNN, convolutional neural network; GAN, generative adversarial network.