Table 2. Comparison of SNR value of background tissue between reconstructed images and real images using 8%PET images as input.

Group	Liver	Lung	Aorta	Lumbar spine
3D Unet-15s	13.42 (10.04, 19.71)*	7.83 (6.10, 8.84)*	15.73 (12.15, 22.36)*	7.69 (6.15, 10.82)
P2P-15s	7.49 (6.66, 10.34)*	3.58 (2.73, 4.36)*	8.14 (7.30, 10.48)	6.29 (5.73, 7.31)
8%PET	2.69 (1.95, 3.28)	2.00 (1.18, 2.14)	2.34 (1.55, 3.01)	1.51 (1.20, 2.26)
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	36.86	40.84	37.06	31.10
P	<0.0001	<0.0001	<0.0001	<0.0001

The italic font represents a statistical difference between this value and that of the 8%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.