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©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
Artif Intell Med Imaging. Apr 28, 2022; 3(2): 42-54
Published online Apr 28, 2022. doi: 10.35711/aimi.v3.i2.42
Published online Apr 28, 2022. doi: 10.35711/aimi.v3.i2.42
Applications of artificial intelligence in lung ultrasound: Review of deep learning methods for COVID-19 fighting
Laura De Rosa, Serena L'Abbate, Claudia Kusmic, Francesco Faita, Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche, Pisa 56124, Italy
Serena L'Abbate, Institute of Life Sciences, Scuola Superiore Sant’Anna, Pisa 56124, Italy
Author contributions: Kusmic C and Faita F designed the research study; Faita F and De Rosa L collected and analysed the references mentioned in the review; De Rosa L wrote the initial draft; Kusmic C, Faita F and L’Abbate S revised and edited the manuscript; all authors have read and approve the final manuscript.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Claudia Kusmic, MSc, PhD, Research Scientist, Institute of Clinical Physiology, Consiglio Nazionale delle Ricerche, Via Giuseppe Moruzzi 1, Pisa 56124, Italy. kusmic@ifc.cnr.it
Received: December 19, 2021
Peer-review started: December 19, 2021
First decision: February 10, 2022
Revised: February 22, 2022
Accepted: April 27, 2022
Article in press: April 27, 2022
Published online: April 28, 2022
Peer-review started: December 19, 2021
First decision: February 10, 2022
Revised: February 22, 2022
Accepted: April 27, 2022
Article in press: April 27, 2022
Published online: April 28, 2022
Core Tip
Core Tip: Challenging coronavirus disease 2019 (COVID-19) pandemic through the identification of effective diagnostic and prognostic tools is of outstanding importance to tackle the healthcare system burdening and improve clinical outcomes. Application of deep learning (DL) in medical lung ultrasound may offer the advantage of combining non-invasiveness and wide accessibility of ultrasound imaging techniques with higher diagnostic performance and classification accuracy. This paper overviews the current applications of DL models in medical lung ultrasound imaging in COVID-19 patients, and highlight the existing challenges associated with the effective clinical application of automated systems in the medical imaging field.