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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Bibliographic Details
Published in:Med Phys
Main Authors: Ouyang, Jiahong, Chen, Kevin T., Gong, Enhao, Pauly, John, Zaharchuk, Greg
Format: Artigo
Language:Inglês
Published: John Wiley and Sons Inc. 2019
Subjects:
QUANTITATIVE IMAGING AND IMAGE PROCESSING
Online Access: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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