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Table 1 Composition of the activity mask dataset (total of 10,000 masks)

From: Analysis of a deep learning-based method for generation of SPECT projections based on a large Monte Carlo simulated dataset

Name of mask Description Sample size
Random shapes Voxelized random shapes 7500
Hot Jaszczak with cold random shapes Inverted version of Random shapes masks. Here, the entire Jaszczak cylinder with the exception of the random shapes is filled with activity 2000
Chessboard pattern Randomly sized squares placed on a randomly sized isotropic 3D grid 100
Rod pattern Rods with randomly large cross sections placed perpendicular to the transverse plane on a randomly sized isotropic 2D grid 100
Cross pattern Randomly sized cross extended along the axial direction 100
Stripe pattern Seven stripes with a thickness varying between 2.4 and 16.8 mm placed perpendicular to the transverse plane 100
NEMA phantom spheres Voxelized activity distribution of the NEMA phantom (six fillable spheres with inner diameters 10/13/17/22/28/37 mm) 100
  1. Before inclusion in the mask, all objects were randomly rotated in the three spatial dimensions (exception: NEMA phantom, random two-dimensional rotation in the transversal plane)