Assisted probe guidance in cardiac ultrasound: A review

• Type: Another Publication in an International Scientific Journal
• Date: 2023

Authors

Ferraz, S (Author) Other; Coimbra, M (Author) FCUP; Pedrosa, J (Author) Other

Journal

Title: Frontiers in Cardiovascular Medicine

Vol. 10

ISSN: 2297-055X

Publisher: Frontiers Media

Indexing

ISI Web of Knowledge - 3 Citations

Scopus

Other information

Authenticus ID: P-00Y-2NV

DOI: 10.3389/fcvm.2023.1056055

Abstract (EN): Echocardiography is the most frequently used imaging modality in cardiology. However, its acquisition is affected by inter-observer variability and largely dependent on the operator's experience. In this context, artificial intelligence techniques could reduce these variabilities and provide a user independent system. In recent years, machine learning (ML) algorithms have been used in echocardiography to automate echocardiographic acquisition. This review focuses on the state-of-the-art studies that use ML to automate tasks regarding the acquisition of echocardiograms, including quality assessment (QA), recognition of cardiac views and assisted probe guidance during the scanning process. The results indicate that performance of automated acquisition was overall good, but most studies lack variability in their datasets. From our comprehensive review, we believe automated acquisition has the potential not only to improve accuracy of diagnosis, but also help novice operators build expertise and facilitate point of care healthcare in medically underserved areas.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9