Pelvic PET/MR attenuation correction in the image space using deep learning

INTRODUCTION: The five-class Dixon-based PET/MR attenuation correction (AC) model, which adds bone information to the four-class model by registering major bones from a bone atlas, has been shown to be error-prone. In this study, we introduce a novel method of accounting for bone in pelvic PET/MR AC...

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Detalles Bibliográficos
Autores principales: Abrahamsen, Bendik Skarre, Knudtsen, Ingerid Skjei, Eikenes, Live, Bathen, Tone Frost, Elschot, Mattijs
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484800/
https://www.ncbi.nlm.nih.gov/pubmed/37692851
http://dx.doi.org/10.3389/fonc.2023.1220009

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484800/
https://www.ncbi.nlm.nih.gov/pubmed/37692851
http://dx.doi.org/10.3389/fonc.2023.1220009

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