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A deep learning approach for (18)F-FDG PET attenuation correction

BACKGROUND: To develop and evaluate the feasibility of a data-driven deep learning approach (deepAC) for positron-emission tomography (PET) image attenuation correction without anatomical imaging. A PET attenuation correction pipeline was developed utilizing deep learning to generate continuously va...

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書目詳細資料
發表在:EJNMMI Phys
Main Authors: Liu, Fang, Jang, Hyungseok, Kijowski, Richard, Zhao, Gengyan, Bradshaw, Tyler, McMillan, Alan B.
格式: Artigo
語言:Inglês
出版: Springer International Publishing 2018
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在線閱讀:https://ncbi.nlm.nih.gov/pmc/articles/PMC6230542/
https://ncbi.nlm.nih.gov/pubmed/30417316
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s40658-018-0225-8
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