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Ultra‐low‐dose PET reconstruction using generative adversarial network with feature matching and task‐specific perceptual loss
PURPOSE: Our goal was to use a generative adversarial network (GAN) with feature matching and task‐specific perceptual loss to synthesize standard‐dose amyloid Positron emission tomography (PET) images of high quality and including accurate pathological features from ultra‐low‐dose PET images only....
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| Gepubliceerd in: | Med Phys |
|---|---|
| Hoofdauteurs: | , , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
John Wiley and Sons Inc.
2019
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6692211/ https://ncbi.nlm.nih.gov/pubmed/31131901 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/mp.13626 |
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