Table 3. Quantitative evaluation of the results of the different methods from Figure 9 for 50 K, 500 K, and 5 M counts.
Methods | 50 K | 500 K | 5 M | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
PSNR | SSIM | rRMSE | PSNR | SSIM | rRMSE | PSNR | SSIM | rRMSE | |||
EM + Gaussian filter | 21.028 | 0.593 | 0.276 | 23 | 0.882 | 0.231 | 26.309 | 0.954 | 0.15 | ||
EM + NLM | 20.165 | 0.651 | 0.304 | 28 | 0.895 | 0.127 | 27.131 | 0.932 | 0.137 | ||
CNN | 21.924 | 0.786 | 0.249 | 30 | 0.926 | 0.104 | 30.595 | 0.938 | 0.092 | ||
GAN | 22.233 | 0.818 | 0.258 | 28 | 0.914 | 0.118 | 32.945 | 0.959 | 0.07 | ||
LCPR-Net | 25.873 | 0.819 | 0.234 | 30 | 0.934 | 0.099 | 33.303 | 0.963 | 0.067 |
PSNR, peak signal-to-noise ratio; SSIM, structural similarity index; rRMSE, relative root mean square error; EM, expectation-maximization; NLM, nonlocal means; CNN, convolutional neural network; GAN, generative adversarial network; LCPR-Net, low-count positron emission tomography image reconstruction network.