Independent attenuation correction of whole body [(18)F]FDG-PET using a deep learning approach with Generative Adversarial Networks

BACKGROUND: Attenuation correction (AC) of PET data is usually performed using a second imaging for the generation of attenuation maps. In certain situations however—when CT- or MR-derived attenuation maps are corrupted or CT acquisition solely for the purpose of AC shall be avoided—it would be of v...

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Detalles Bibliográficos
Autores principales: Armanious, Karim, Hepp, Tobias, Küstner, Thomas, Dittmann, Helmut, Nikolaou, Konstantin, La Fougère, Christian, Yang, Bin, Gatidis, Sergios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246235/
https://www.ncbi.nlm.nih.gov/pubmed/32449036
http://dx.doi.org/10.1186/s13550-020-00644-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246235/
https://www.ncbi.nlm.nih.gov/pubmed/32449036
http://dx.doi.org/10.1186/s13550-020-00644-y

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