Deep learning for opportunistic, end-to-end automated assessment of epicardial adipose tissue in pre-interventional, ECG-gated spiral computed tomography

Abstract Objectives Recently, epicardial adipose tissue (EAT) assessed by CT was identified as an independent mortality predictor in patients with various cardiac diseases. Our goal was to develop a deep learning pipeline for robust automatic EAT assessment in CT. Methods Contrast-enhanced ECG-gated...

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Autors principals:	Maike Theis, Laura Garajová, Babak Salam, Sebastian Nowak, Wolfgang Block, Ulrike I. Attenberger, Daniel Kütting, Julian A. Luetkens, Alois M. Sprinkart
Format:	Artigo
Idioma:	Inglês
Publicat:	SpringerOpen 2024-12-01
Col·lecció:	Insights into Imaging
Matèries:	Epicardial adipose tissue Transcatheter aortic valve replacement Tomography (X-ray computed) Deep learning
Accés en línia:	https://doi.org/10.1186/s13244-024-01875-6
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