Leydon, PatrickPatrickLeydonO'Connell, MartinMartinO'ConnellGreene, DerekDerekGreeneCurran, Kathleen M.Kathleen M.Curran2020-05-052020-05-052019-08-30978 0 9934207 4 0http://hdl.handle.net/10197/11361The 2019 Irish Machine Vision and Image Processing (IMVIP 2019), Technological University Dublin, Irealnd, 28-30 August 2019A Conditional-Generative Adversarial Network has been used for a supervised image-to-image translation task which outputs a synthetic PET scan based on real patient CT data. The network is trained using only data of patients with healthy bone marrow metabolism. This allows for a patient specific synthetic healthy baseline scan to be produced. This can be used by a clinician for comparison to real PET data in the absence of a baseline scan or to aid in the diagnosis of conditions such as Multiple Myeloma which manifest as changes in bone marrow metabolismenMedical imagingConditional-generative adversarial networksDeep learningPET-CTBone marrowConference Publication2019-10-31https://creativecommons.org/licenses/by-nc-nd/3.0/ie/