Synthetic 18F-FDG PET Image Generation Using a Combination of Biomathematical Modeling and Machine Learning

SIMPLE SUMMARY: Training computer-assisted algorithms on medical images, particularly 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) due to its excellent diagnostic accuracy, is difficult, considering small/fragmented samples or privacy concerns. In computer-vision, deep learnin...

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Detalles Bibliográficos
Autores principales: Abazari, Mohammad Amin, Soltani, Madjid, Moradi Kashkooli, Farshad, Raahemifar, Kaamran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9179454/
https://www.ncbi.nlm.nih.gov/pubmed/35681767
http://dx.doi.org/10.3390/cancers14112786

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9179454/
https://www.ncbi.nlm.nih.gov/pubmed/35681767
http://dx.doi.org/10.3390/cancers14112786

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