Post-reconstruction enhancement of [(18)F]FDG PET images with a convolutional neural network

BACKGROUND: The aim of the study was to develop and test an artificial intelligence (AI)-based method to improve the quality of [(18)F]fluorodeoxyglucose (FDG) positron emission tomography (PET) images. METHODS: A convolutional neural network (CNN) was trained by using pairs of excellent (acquisitio...

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Detalles Bibliográficos
Autores principales: Ly, John, Minarik, David, Jögi, Jonas, Wollmer, Per, Trägårdh, Elin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113431/
https://www.ncbi.nlm.nih.gov/pubmed/33974171
http://dx.doi.org/10.1186/s13550-021-00788-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113431/
https://www.ncbi.nlm.nih.gov/pubmed/33974171
http://dx.doi.org/10.1186/s13550-021-00788-5

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