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Table 2 PSNR and SSIM indices variation in comparison to PET100, considering the slice with all visible spheres from the NEMA IEC phantom experiments (E1 & E2)

From: Clinical and phantom validation of a deep learning based denoising algorithm for F-18-FDG PET images from lower detection counting in comparison with the standard acquisition

  PET50 PET50 + SP PET33 PET33 + SP
PSNR (E1)     
D710 41.61 43.07 36.55 37.42
IQ4 38.86 40.30 37.81 40.26
DMI4 38.53 40.19 33.12 33.88
PSNR (E2)     
D710 35.60 36.73 35.82 39.29
IQ4 39.27 40.92 34.85 36.98
DMI4 34.71 39.26 30.98 35.04
SSIM (E1)     
D710 0.982 0.984 0.972 0.976
IQ4 0.979 0.983 0.968 0.977
DMI4 0.983 0.987 0.968 0.973
SSIM (E2)     
D710 0.980 0.981 0.968 0.975
IQ4 0.980 0.983 0.972 0.978
DMI4 0.976 0.980 0.964 0.972
  1. SubtlePET processing increase the PSNR & SSIM in every instance i.e., PET50 & PET33 images