Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation
|Title:||Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation||Authors:||Leydon, Patrick; O'Connell, Martin; Greene, Derek; Curran, Kathleen M.||Permanent link:||http://hdl.handle.net/10197/11361||Date:||30-Aug-2019||Online since:||2020-05-05T10:26:11Z||Abstract:||A 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 metabolism||Funding Details:||Science Foundation Ireland||metadata.dc.description.othersponsorship:||Insight Research Centre||Type of material:||Conference Publication||Keywords:||Medical imaging; Conditional-generative adversarial networks; Deep learning; PET-CT; Bone marrow||Other versions:||http://www.imvip.ie/
|Language:||en||Status of Item:||Peer reviewed||Conference Details:||The 2019 Irish Machine Vision and Image Processing (IMVIP 2019), Technological University Dublin, Irealnd, 28-30 August 2019||ISBN:||978 0 9934207 4 0|
|Appears in Collections:||Insight Research Collection|
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