  PETALO (Positron Emission TOF Apparatus based on Liquid xenOn) exploits the
unique characteristics of liquid xenon as a scintillator for use in a PET
detector. Here initial simulation studies are detailed which highlight the
potential of such a detector and outline the steps taken in the reconstruction
of 511 keV gamma rays and in the full PET image reconstruction. In particular,
a neural network-based approach is conceived in order to tag gamma rays that
are poorly reconstructed due to Compton scattering. It is found that though a
significant fraction of events undergo Compton scattering, not all of these
events will necessarily be poorly reconstructed. Further study is necessary to
determine whether or not an online implementation of the neural network-based
event tagging will provide sufficient recovery of the image quality.
