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Deep learning-based Attenuation Correction in the Absence of Structural Information for Whole-body PET Imaging

Deriving accurate structural maps for attenuation correction (AC) of whole-body PET remains challenging. Common problems include truncation, inter-scan motion, and erroneous transformation of structural voxel-intensities to PET μ-map values (e.g. modality artifacts, implanted devices, or contrast ag...

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Bibliografiske detaljer
Udgivet i:Phys Med Biol
Main Authors: Dong, Xue, Lei, Yang, Wang, Tonghe, Higgins, Kristin, Liu, Tian, Curran, Walter J., Mao, Hui, Nye, Jonathon A., Yang, Xiaofeng
Format: Artigo
Sprog:Inglês
Udgivet: 2020
Fag:
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7099429/
https://ncbi.nlm.nih.gov/pubmed/31869826
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1088/1361-6560/ab652c
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