Evaluation of AI-Based Segmentation Tools for COVID-19 Lung Lesions on Conventional and Ultra-low Dose CT Scans.

Publication Year: 2022

DOI:
10.1177/15593258221082896

PMCID:
PMC9002358

PMID:
35422680

Journal Information

Full Title: Dose Response

Abbreviation: Dose Response

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
3/6
50.0% Transparent
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"Declaration of Conflicting Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article."

Evidence found in paper:

"Funding: The authors disclosed receipt of the following financial support for the research, authorship, and publication of this article: This work was partially funded by the Italian Ministry of Health for the “Ricerca Corrente” project and by POR CAMPANIA FESR 2014 - 2020 for the “Protocolli TC del torace a bassissima dose e tecniche di intelligenza artificiale per la diagnosi precoce e quantificazione della malattia da COVID-19” project."

Protocol Registration
Open Access
Paper is freely available to read
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OST Version: N/A

Last Updated: Aug 05, 2025