Convolutional neural networks for automatic image quality control and EARL compliance of PET images.

Publication Year: 2022

DOI:
10.1186/s40658-022-00468-w

PMCID:
PMC9363539

PMID:
35943622

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

Transparency Score
5/6
83.3% Transparent
Transparency Indicators
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Core Indicators
Evidence found in paper:

"to make the methods and results publicly available a python script that takes one image or a series of nifty images as input and displays the corresponding reconstruction setting is available on zenodo and can be used by the community. table 1 . all data"

Evidence found in paper:

"to make the methods and results publicly available a python script that takes one image or a series of nifty images as input and displays the corresponding reconstruction setting is available on zenodo and can be used by the community."

Evidence found in paper:

"Declarations Ethics approval and consent to participateAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. 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 Open Access funding enabled and organized by Projekt DEAL."

Protocol Registration
Open Access
Paper is freely available to read
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Assessment Info

Tool: rtransparent

OST Version: N/A

Last Updated: Aug 05, 2025