Deep learning of echocardiography distinguishes between presence and absence of late gadolinium enhancement on cardiac magnetic resonance in patients with hypertrophic cardiomyopathy

Akita, K., Kusunose, K., Haga, A., Shimomura, T., Kosaka, Y., Ishiyama, K., Hasegawa, K., Fifer, M. A., Maurer, M. S., & Shimada, Y. J. (2024). Deep learning of echocardiography distinguishes between presence and absence of late gadolinium enhancement on cardiac magnetic resonance in patients with hypertrophic cardiomyopathy. Echo Research & Practice, 11(1). https://doi.org/10.1186/s44156-024-00059-8
Authors:
Keitaro Akita
Kenya Kusunose
Akihiro Haga
Taisei Shimomura
Yoshitaka Kosaka
Katsunori Ishiyama
Kohei Hasegawa
Michael A Fifer
Mathew S Maurer
Yuichi J Shimada
Affiliated Authors:
Keitaro Akita
Mathew S Maurer
Yuichi J Shimada
Columbia Affiliation:
Subjects:
Diagnosis and Management of Hypertrophic Cardiomyopathy (OpenAlex Topic)
Recommendations for Cardiac Chamber Quantification by Echocardiography (OpenAlex Topic)
Epidemiology and Management of Congenital Heart Disease (OpenAlex Topic)
Author Keywords:
cardiac magnetic resonance
deep learning
echocardiography
hypertrophic cardiomyopathy
late gadolinium enhancement
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Publication Type:
Article
Unique ID:
10.1186/s44156-024-00059-8
PMID:
39396969
DOI:
10.1186/s44156-024-00059-8
Journal:
Echo Research and Practice
Publication Date:
Data Source:
PubMed
Source Link:
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Record Created: