The training set used for FlowNet-PET found in https://github.com/teaghan/FlowNet_PET A dataset of 300 phantoms generated using the 4D extended cardiac-torso (XCAT) anthropomorphic digital phantom (2x4x4) mm3 voxels. The dataset is split into training (270) and validation (30) sets. For each phantom, ten frames spaced across a single breath cycle were created, each frame having (108x152x152) pixels resembling the activity distribution throughout the phantom. To emulate a simple representation of PET data acquisition, these distributions were used to sample a random number (between 1x106 and 9x106) of counts per frame. The parameters for each XCAT phantom were varied randomly. This included the gender, axial section included, transaxial shifts, scaling factors in each direction, size and location of the lung lesion, extent of the diaphragm motion, extent of the chest expansion, and the activity of each organ.