A deep learning-based whole-body solution for PET/MRI attenuation correction.

Authors:
Ahangari S; Beck Olin A; Kinggård Federspiel M; Jakoby B; Andersen TL and 3 more

Journal:
EJNMMI Phys

Publication Year: 2022

DOI:
10.1186/s40658-022-00486-8

PMCID:
PMC9385907

PMID:
35978211

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Journal Information

Full Title: EJNMMI Phys

Abbreviation: EJNMMI Phys

Country: Unknown

Publisher: Unknown

Language: N/A

Publication Details

Subject Category: Radiology, Nuclear Medicine & Medical Imaging

Available in Europe PMC: Yes

Available in PMC: Yes

PDF Available: No

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"Declarations Ethics approval and consent to participateThe data were collected as prospective quality assurance and approved by the local ethics committee. All patients gave written informed consent to participate. Consent for publicationNot applicable. Competing interestsThe authors declare that they have no competing interests. Competing interests The authors declare that they have no competing interests."

Evidence found in paper:

"Funding This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No 764458."

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Last Updated: Aug 05, 2025