Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation

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Title: Synthetic Positron Emission Tomography Using Conditional-Generative Adversarial Networks for Healthy Bone Marrow Baseline Image Generation
Authors: Leydon, PatrickO'Connell, MartinGreene, DerekCurran, 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 imagingConditional-generative adversarial networksDeep learningPET-CTBone marrow
Other versions: http://www.imvip.ie/
https://arrow.dit.ie/ditpress/11/
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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