Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners

PURPOSE: Attenuation correction is a critically important step in data correction in positron emission tomography (PET) image formation. The current standard method involves conversion of Hounsfield units from a computed tomography (CT) image to construct attenuation maps (µ-maps) at 511 keV. In thi...

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Detalles Bibliográficos
Autores principales: Sari, Hasan, Teimoorisichani, Mohammadreza, Mingels, Clemens, Alberts, Ian, Panin, Vladimir, Bharkhada, Deepak, Xue, Song, Prenosil, George, Shi, Kuangyu, Conti, Maurizio, Rominger, Axel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606046/
https://www.ncbi.nlm.nih.gov/pubmed/35852557
http://dx.doi.org/10.1007/s00259-022-05909-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606046/
https://www.ncbi.nlm.nih.gov/pubmed/35852557
http://dx.doi.org/10.1007/s00259-022-05909-3

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