For each batch, we ran 5,000 epochs, which took ca. 5.28 h excluding the initialization time. To improve image quality and reduce the number of required epochs, we pre-trained the generator using FBP images from 180 °projections. This preliminary step required only 1,000 iterations and was completed in 4 min for each batch. In total, the image reconstruction with ParallaxNet took ca. 16.43 h. The ParallaxNet training was performed using a workstation equipped with an NVIDIA Quadro RTX8000 GPU, Intel Xeon W-2155 CPU at 3.30GHz and using PyTorch version 1.13.1.