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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


Sample size

Random shapes

Voxelized random shapes


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


Chessboard pattern

Randomly sized squares placed on a randomly sized isotropic 3D grid


Rod pattern

Rods with randomly large cross sections placed perpendicular to the transverse plane on a randomly sized isotropic 2D grid


Cross pattern

Randomly sized cross extended along the axial direction


Stripe pattern

Seven stripes with a thickness varying between 2.4 and 16.8 mm placed perpendicular to the transverse plane


NEMA phantom spheres

Voxelized activity distribution of the NEMA phantom (six fillable spheres with inner diameters 10/13/17/22/28/37 mm)


  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)