Image enhancement of whole-body oncology [(18)F]-FDG PET scans using deep neural networks to reduce noise

PURPOSE: To enhance the image quality of oncology [(18)F]-FDG PET scans acquired in shorter times and reconstructed by faster algorithms using deep neural networks. METHODS: List-mode data from 277 [(18)F]-FDG PET/CT scans, from six centres using GE Discovery PET/CT scanners, were split into ¾-, ½-...

Descripción completa

Detalles Bibliográficos
Autores principales: Mehranian, Abolfazl, Wollenweber, Scott D., Walker, Matthew D., Bradley, Kevin M., Fielding, Patrick A., Su, Kuan-Hao, Johnsen, Robert, Kotasidis, Fotis, Jansen, Floris P., McGowan, Daniel R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8803788/
https://www.ncbi.nlm.nih.gov/pubmed/34318350
http://dx.doi.org/10.1007/s00259-021-05478-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8803788/
https://www.ncbi.nlm.nih.gov/pubmed/34318350
http://dx.doi.org/10.1007/s00259-021-05478-x

Ejemplares similares